latest research topics in image processing 2023

Showing papers on "Image processing published in 2023"

Ieee transactions on image processing.

123  citations

Image Processing On Line

13  citations

SNIS: A Signal Noise Separation-Based Network for Post-Processed Image Forgery Detection

4  citations

Deep learning-based real-world object detection and improved anomaly detection for surveillance videos

3  citations

Noncontact Sensing Techniques for AI-Aided Structural Health Monitoring: A Systematic Review

Automatic seat identification system in smart transport using iot and image processing, practical application of digital image processing in measuring concrete crack widths in field studies.

2  citations

Saliency map in image visual quality assessment and processing

Integrated diffusion image operator (idio): a pipeline for automated configuration and processing of diffusion mri data, development of complete image processing system including image filtering, image compression & image security, android-based herpes disease detection application using image processing, automated invoice data extraction using image processing, efficient object detection and classification approach using htyolov4 and m2rfo-cnn, deep and low-rank quaternion priors for color image processing, implementation of automated pipeline for resting-state fmri analysis with pacs integration, stress detection using machine learning and image processing, automated extraction of seed morphological traits from images, identification of counterfeit indian currency note using image processing and machine learning classifiers, computer vision on x-ray data in industrial production and security applications: a comprehensive survey, iot based image processing filters, comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects., research on super-resolution image based on deep learning, ocr-mrd: performance analysis of different optical character recognition engines for medical report digitization, joint graph attention and asymmetric convolutional neural network for deep image compression, brain tumor diagnosis using image fusion and deep learning, brain tumor diagnosis using machine learning: a review, a study of air-water flow in a narrow rectangular duct using an image processing technique, deep learning using a residual deconvolutional network enables real-time high-density single-molecule localization microscopy., improved frqi on superconducting processors and its restrictions in the nisq era, darsia: an open-source python toolbox for two-scale image processing of dynamics in porous media.

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Image processing articles within Scientific Reports

Article 10 September 2024 | Open Access

Ultrasound based radiomics model for assessment of placental function in pregnancies with preeclampsia

• Hongshuang Sun
• , Jing Jiao
•  &  Yunyun Ren

Article 06 September 2024 | Open Access

A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection

• Zicong Yang
• , Aitong Jin
•  &  Yan Liu

Article 05 September 2024 | Open Access

Computer vision for kinematic metrics of the drinking task in a pilot study of neurotypical participants

• Justin Huber
• , Stacey Slone
•  &  Jihye Bae

A multicentre study to evaluate the diagnostic performance of a novel CAD software, DecXpert, for radiological diagnosis of tuberculosis in the northern Indian population

• , Zia Hashim
•  &  Ankit Shukla

An encryption algorithm for color images based on an improved dual-chaotic system combined with DNA encoding

• , Tingting Liu
•  &  Jun Yin

Article 04 September 2024 | Open Access

Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning

• Seung Hwan Lee
• , Jisu Jeon
•  &  Kwang Gi Kim

Article 03 September 2024 | Open Access

A multi-task deep learning approach for real-time view classification and quality assessment of echocardiographic images

• , Hongmei Zhang
•  &  Shenghua Xie

Article 02 September 2024 | Open Access

Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA

• Julia Schottenhamml
• , Tobias Würfl
•  &  Christian Mardin

Article 31 August 2024 | Open Access

A differential network with multiple gated reverse attention for medical image segmentation

• , Benquan Yang
•  &  Aihua Chen

Article 29 August 2024 | Open Access

Adaptive condition-aware high-dimensional decoupling remote sensing image object detection algorithm

• Chenshuai Bai
• , Xiaofeng Bai
•  &  Yuanjie Ye

Article 28 August 2024 | Open Access

Deep learning-assisted segmentation of X-ray images for rapid and accurate assessment of foot arch morphology and plantar soft tissue thickness

• , Tianhong Ru
•  &  Ran Huang

A mixed Mamba U-net for prostate segmentation in MR images

• , Luowu Wang
•  &  Hao Chen

Article 26 August 2024 | Open Access

Multiwell-based G0-PCC assay for radiation biodosimetry

• Ekaterina Royba
• , Igor Shuryak
•  &  David J. Brenner

Article 24 August 2024 | Open Access

Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans

• Chattapatr Leeraha
• , Worapan Kusakunniran
•  &  Thanongchai Siriapisith

Article 23 August 2024 | Open Access

Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure

• Jovana Paunovic Pantic
• , Danijela Vucevic
•  &  Igor Pantic

Article 21 August 2024 | Open Access

An efficient segment anything model for the segmentation of medical images

• Guanliang Dong
• , Zhangquan Wang
•  &  Haidong Cui

Article 20 August 2024 | Open Access

A novel approach for automatic classification of macular degeneration OCT images

• Shilong Pang
• , Beiji Zou
•  &  Kejuan Yue

Article 18 August 2024 | Open Access

Subject-specific atlas for automatic brain tissue segmentation of neonatal magnetic resonance images

• Negar Noorizadeh
• , Kamran Kazemi
•  &  Ardalan Aarabi

Article 17 August 2024 | Open Access

Three layered sparse dictionary learning algorithm for enhancing the subject wise segregation of brain networks

• Muhammad Usman Khalid
• , Malik Muhammad Nauman
•  &  Kamran Ali

Article 14 August 2024 | Open Access

Development and performance evaluation of fully automated deep learning-based models for myocardial segmentation on T1 mapping MRI data

• Mathias Manzke
• , Simon Iseke
•  &  Felix G. Meinel

Article 13 August 2024 | Open Access

Haemodynamic study of left nonthrombotic iliac vein lesions: a preliminary report

• , Qijia Liu
•  &  Xuan Li

Cross-modality sub-image retrieval using contrastive multimodal image representations

• Eva Breznik
• , Elisabeth Wetzer
•  &  Nataša Sladoje

Article 11 August 2024 | Open Access

Effective descriptor extraction strategies for correspondence matching in coronary angiography images

• Hyun-Woo Kim
• , Soon-Cheol Noh
•  &  Si-Hyuck Kang

Article 10 August 2024 | Open Access

Lightweight safflower cluster detection based on YOLOv5

• , Tianlun Wu
•  &  Haiyang Chen

Article 08 August 2024 | Open Access

Primiparous sow behaviour on the day of farrowing as one of the primary contributors to the growth of piglets in early lactation

• Océane Girardie
• , Denis Laloë
•  &  Laurianne Canario

High-throughput image processing software for the study of nuclear architecture and gene expression

• Adib Keikhosravi
• , Faisal Almansour
•  &  Gianluca Pegoraro

Article 07 August 2024 | Open Access

Puzzle: taking livestock tracking to the next level

• Jehan-Antoine Vayssade
•  &  Mathieu Bonneau

Article 02 August 2024 | Open Access

The impact of fine-tuning paradigms on unknown plant diseases recognition

• Jiuqing Dong
• , Alvaro Fuentes
•  &  Dong Sun Park

Article 01 August 2024 | Open Access

AI-enhanced real-time cattle identification system through tracking across various environments

• Su Larb Mon
• , Tsubasa Onizuka
•  &  Thi Thi Zin

Article 31 July 2024 | Open Access

Study on lung CT image segmentation algorithm based on threshold-gradient combination and improved convex hull method

• Junbao Zheng
• , Lixian Wang
•  &  Abdulla Hamad Yussuf

Article 30 July 2024 | Open Access

A multibranch and multiscale neural network based on semantic perception for multimodal medical image fusion

• , Yinjie Chen
•  &  Mengxing Huang

Article 26 July 2024 | Open Access

Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning

• Benjamin C. Musall
• , Refaat E. Gabr
•  &  Khader M. Hasan

The integrity of the corticospinal tract and corpus callosum, and the risk of ALS: univariable and multivariable Mendelian randomization

• , Gan Zhang
•  &  Dongsheng Fan

Article 23 July 2024 | Open Access

Accelerating photoacoustic microscopy by reconstructing undersampled images using diffusion models

•  &  M. Burcin Unlu

Article 20 July 2024 | Open Access

Automated segmentation of the median nerve in patients with carpal tunnel syndrome

• Florentin Moser
• , Sébastien Muller
•  &  Mari Hoff

Article 18 July 2024 | Open Access

Estimating infant age from skull X-ray images using deep learning

• Heui Seung Lee
• , Jaewoong Kang
•  &  Bum-Joo Cho

Article 17 July 2024 | Open Access

Finite element models with automatic computed tomography bone segmentation for failure load computation

• Emile Saillard
• , Marc Gardegaront
•  &  Hélène Follet

Article 16 July 2024 | Open Access

Deep learning pose detection model for sow locomotion

• Tauana Maria Carlos Guimarães de Paula
• , Rafael Vieira de Sousa
•  &  Adroaldo José Zanella

Article 15 July 2024 | Open Access

Deep learning application of vertebral compression fracture detection using mask R-CNN

• Seungyoon Paik
• , Jiwon Park
•  &  Sung Won Han

Article 11 July 2024 | Open Access

Morphological classification of neurons based on Sugeno fuzzy integration and multi-classifier fusion

• , Guanglian Li
•  &  Haixing Song

Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis

• , Feng Xiao
•  &  Haibo Xu

Article 09 July 2024 | Open Access

Noninvasive, label-free image approaches to predict multimodal molecular markers in pluripotency assessment

• Ryutaro Akiyoshi
• , Takeshi Hase
•  &  Ayako Yachie

Article 08 July 2024 | Open Access

A prospective multi-center study quantifying visual inattention in delirium using generative models of the visual processing stream

• Ahmed Al-Hindawi
• , Marcela Vizcaychipi
•  &  Yiannis Demiris

Article 06 July 2024 | Open Access

Advancing common bean ( Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI

• Daniela Gomez
• , Michael Gomez Selvaraj
•  &  Ernesto Espitia

Article 05 July 2024 | Open Access

Image processing based modeling for Rosa roxburghii fruits mass and volume estimation

• Zhiping Xie
• , Junhao Wang
•  &  Manyu Sun

On leveraging self-supervised learning for accurate HCV genotyping

• Ahmed M. Fahmy
• , Muhammed S. Hammad
•  &  Walid I. Al-atabany

A semantic feature enhanced YOLOv5-based network for polyp detection from colonoscopy images

• Jing-Jing Wan
• , Peng-Cheng Zhu
•  &  Yong-Tao Yu

Article 03 July 2024 | Open Access

DSnet: a new dual-branch network for hippocampus subfield segmentation

• , Wangang Cheng
•  &  Guanghua He

Quantification of cardiac capillarization in basement-membrane-immunostained myocardial slices using Segment Anything Model

• , Xiwen Chen
•  &  Tong Ye

Article 02 July 2024 | Open Access

Matrix metalloproteinase 9 expression and glioblastoma survival prediction using machine learning on digital pathological images

• , Yuan Yang
•  &  Yunfei Zha

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Top 10 Digital Image Processing Project Topics

We guide research scholars in choosing novel digital image processing project topics. What is meant by digital image processing? Digital Image Processing is a method of handling images to get different insights into the digital image. It has a set of technologies to analyze the image in multiple aspects for better human / machine image interpretation . To be clearer, it is used to improve the actual quality of the image or to abstract the essential features from the entire picture is achieved through digital image processing projects.

This page is about the new upcoming Digital Image Processing Project Topics for scholars who wish to create a masterpiece in their research career!!!

Generally, the digital image is represented in the form of pixels which are arranged in array format. The dimension of the rectangular array gives the size of the image (MxN), where M denotes the column and N denotes the row. Further, x and y coordinates are used to signify the single-pixel position of an image. At the same time, the x value increases from left to right, and the y value increases from top to bottom in the coordinate representation of the image. When you get into the DIP research field, you need to know the following key terminologies.

Important Digital Image Processing Terminologies  

• Stereo Vision and Super Resolution
• Multi-Spectral Remote Sensing and Imaging
• Digital Photography and Imaging
• Acoustic Imaging and Holographic Imaging
• Computer Vision and Graphics
• Image Manipulation and Retrieval
• Quality Enrichment in Volumetric Imaging
• Color Imaging and Bio-Medical Imaging
• Pattern Recognition and Analysis
• Imaging Software Tools, Technologies and Languages
• Image Acquisition and Compression Techniques
• Mathematical Morphological Image Segmentation

Image Processing Algorithms

In general, image processing techniques/methods are used to perform certain actions over the input images, and according to that, the desired information is extracted in it. For that, input is an image, and the result is an improved/expected image associated with their task. It is essential to find that the algorithms for image processing play a crucial role in current real-time applications. Various algorithms are used for various purposes as follows, 

• Digital Image Detection
• Image Reconstruction
• Image Restoration
• Image Enhancement
• Image Quality Estimation
• Spectral Image Estimation
• Image Data Compression

For the above image processing tasks, algorithms are customized for the number of training and testing samples and also can be used for real-time/online processing. Till now, filtering techniques are used for image processing and enhancement, and their main functions are as follows, 

• Brightness Correction
• Contrast Enhancement
• Resolution and Noise Level of Image
• Contouring and Image Sharpening
• Blurring, Edge Detection and Embossing

Some of the commonly used techniques for image processing can be classified into the following, 

• Medium Level Image Processing Techniques – Binarization and Compression
• Higher Level Image Processing Techniques – Image Segmentation
• Low-Level Image Processing Techniques – Noise Elimination and Color Contrast Enhancement
• Recognition and Detection Image Processing Algorithms – Semantic Analysis

Next, let’s see about some of the traditional image processing algorithms for your information. Our research team will guide in handpicking apt solutions for research problems . If there is a need, we are also ready to design own hybrid algorithms and techniques for sorting out complicated model . 

Types of Digital Image Processing Algorithms

• Hough Transform Algorithm
• Canny Edge Detector Algorithm
• Scale-Invariant Feature Transform (SIFT) Algorithm
• Generalized Hough Transform Algorithm
• Speeded Up Robust Features (SURF) Algorithm
• Marr–Hildreth Algorithm
• Connected-component labeling algorithm: Identify and classify the disconnected areas
• Histogram equalization algorithm: Enhance the contrast of image by utilizing the histogram
• Adaptive histogram equalization algorithm: Perform slight alteration in contrast for the  equalization of the histogram
• Error Diffusion Algorithm
• Ordered Dithering Algorithm
• Floyd–Steinberg Dithering Algorithm
• Riemersma Dithering Algorithm
• Richardson–Lucy deconvolution algorithm : It is also known as a deblurring algorithm, which removes the misrepresentation of the image to recover the original image
• Seam carving algorithm : Differentiate the edge based on the image background information and also known as content-aware image resizing algorithm
• Region Growing Algorithm
• GrowCut Algorithm
• Watershed Transformation Algorithm
• Random Walker Algorithm
• Elser difference-map algorithm: It is a search based algorithm primarily used for X-Ray diffraction microscopy to solve the general constraint satisfaction problems
• Blind deconvolution algorithm : It is similar to Richardson–Lucy deconvolution to reconstruct the sharp point of blur image. In other words, it’s the process of deblurring the image.

Nowadays, various industries are also utilizing digital image processing by developing customizing procedures to satisfy their requirements. It may be achieved either from scratch or hybrid algorithmic functions . As a result, it is clear that image processing is revolutionary developed in many information technology sectors and applications.  

Digital Image Processing Techniques

• In order to smooth the image, substitutes neighbor median / common value in the place of the actual pixel value. Whereas it is performed in the case of weak edge sharpness and blur image effect.
• Eliminate the distortion in an image by scaling, wrapping, translation, and rotation process
• Differentiate the in-depth image content to figure out the original hidden data or to convert the color image into a gray-scale image
• Breaking up of image into multiple forms based on certain constraints. For instance: foreground, background
• Enhance the image display through pixel-based threshold operation 
• Reduce the noise in an image by the average of diverse quality multiple images 
• Sharpening the image by improving the pixel value in the edge
• Extract the specific feature for removal of noise in an image
• Perform arithmetic operations (add, sub, divide and multiply) to identify the variation in between the images 

Beyond this, this field will give you numerous Digital Image Processing Project Topics for current and upcoming scholars . Below, we have mentioned some research ideas that help you to classify analysis, represent and display the images or particular characteristics of an image.

Latest 11 Interesting Digital Image Processing Project Topics

• Acoustic and Color Image Processing
• Digital Video and Signal Processing
• Multi-spectral and Laser Polarimetric Imaging
• Image Processing and Sensing Techniques
• Super-resolution Imaging and Applications
• Passive and Active Remote Sensing
• Time-Frequency Signal Processing and Analysis
• 3-D Surface Reconstruction using Remote Sensed Image
• Digital Image based Steganalysis and Steganography
• Radar Image Processing for Remote Sensing Applications
• Adaptive Clustering Algorithms for Image processing

Moreover, if you want to know more about Digital Image Processing Project Topics for your research, then communicate with our team. We will give detailed information on current trends, future developments, and real-time challenges in the research grounds of Digital Image Processing.

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6th International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R)

December 07-08, 2023, university in derby, england (uk), ... in collaboration with 2ai: applied ai research lab , usd (usa).

• Registration
• Special track

Important dates

Full paper submission: july 15 august 15 august 31, 2023 notification (sent to authors): august 31 september 15 october 10, 2023 registration: august 15 september 15 september 30 october 10 october 20, 2023 camera ready submission: august 31 september 30 october 15 october 30, 2023, publications, conference proceedings: ccis, springer nature indexing: dblp, ei compendex, inspec, scimago, scopus, zbmath, and many other databases, journal publications (special issue): ijprai , electronics, keynote speakers, girijesh prasad, phd professor school of computing, engineering and intelligent systems ulster university (uu), uk., workshop speakers, kc santosh, phd chair, department of computer science university of south dakota (usa), wajahat ali khan, phd associate professor university of derby (uk), vinaytosh mishra , phd associate professor college of healthcare management and economic gulf medical university, ajman (uae), dr mabrouka abuhmida , phd research and innovation group leader university of south wales (uk), previous publications, 2022 (conference proceedings): ccis, springer : vol. 1704 2021 (conference proceedings): ccis, springer : vol. 1576 2020 (conference proceedings): ccis, springer : vol. 1380 , vol. 1381 2018 (journal issue): vol. 79 issue 47 mtap, springer nature (2020) 2018 (conference proceedings): ccis, springer : vol. 1035 , vol. 1036 , and vol. 1037 (2019) 2016 (journal issue): vol. 7, issue 2, ijcvip, igi global (2017) 2016 (conference proceedings): ccis, springer , vol. 709 (2017), would you like to join us (e.g., technical program committee) do not hesitate to contact us (general and program chairs), total page visits.

Program schedule: PDF

Accomodation.

To facilitate the booking process for conference attendees, they can make reservations directly through the following link and use the postcode DE1 3LD (Enterprise Centre) to find nearby accommodation. Link for Booking T his convenient option allows attendees to quickly access information and book accommodations that best suit their needs. Kindly contact Muntazir Mehdi (local organiser) at [email protected] or +44-7762253211 , if you have any questions or concerns related to accommodation during conference.

Conference Venue and Presentation Sessions

As the RTIP2R 2023 Conference approaches, we are reaching out to kindly inform you about the conference venue and presentation sessions schedule.Each author presentation is allocated 10 minutes in total, with 8 minutes for the main content and 2 minutes dedicated to Q&A. The authors who will be presenting in-person are requested to submit their presentation slides to the conference at [email protected] In-person presentation: Venue: Conference room: G11, G12, Enterprise Centre, Bridge St, Derby, DE1 3LD Presentation duration: 10 minutes Q/A: 2 minutes Session: Available in program schedule Online presentation: Venue: Microsoft Teams link below. Presentation duration: 8 minutes Q/A: 2 minutes Session: Available in program schedule 7th December: G11- Main hall: 10am-3pm (session 1, session 2) Meeting ID: 313 318 656 333 Passcode: 5Xh6QB 3pm-6pm (session 3, session 5) Meeting ID: 332 759 420 087 Passcode: uLtNqV G13- 3pm-6pm (session 4, session 6) Meeting ID: 367 091 083 468 Passcode: iGYUWB 8th December: G11- Main hall: 10am-2:30pm (workshop + session 7) Meeting ID: 323 565 100 074 Passcode: Ey8Zhz 2:30pm - 6:30pm (session 8, session 10) Meeting ID: 311 148 200 419 Passcode: 8CHeMS G13- 2:30 pm- 6:30pm (session 9, session 11) Meeting ID: 392 506 549 396 Passcode: nXQN7j Announcement Following events, best paper awards, and many more. Concluding remarks 6pm- 7pm Meeting ID: 330 620 894 679 Passcode: MYe6k6 As the conference is taking place in the UK, all scheduled times will be in the UK time zone, GMT. Your presentation will contribute significantly to the enriching discussions and knowledge exchange at RTIP2R 2023. We expect engaging content that highlights your research and insights within the time limit provided.

Welcome to the RTIP2R 2023

Topics of interest include, but are not limited to.

    • Signal, image processing, and machine learning : Signal processing, image analysis fundamentals, algorithms, clustering and classification, model selection (ma chine learning), feature engineering, federated learning, and shallow as well as deep learning.     • Computer vision & pattern recognition : Object detection and/or recognition (shape, color and texture analysis) and pattern recognition (statistical, structural, and syntactic methods).     • Machine learning : Algorithms, clustering and classification, model selection (ma chine learning), feature engineering, deep learning, and federated Learning (applications and challenges).     • Data science/analytics : Data mining tools, high-performance computing in big data. Link to all the special tracks is here .

Journal publications (special issue)

    • Explainable and/or Interpretable AI for Biomedical and Health Informatics, International Journal of Pattern Recognition & Artificial Intelligence ( IJPRAI ) ( Download file ).     • Recent Trends in Image Processing and Pattern Recognition, Electronics - Computer Science & Engineering section, MDPI. ( electronics ) ( Download file ).

Competitions

Fractured bone detection challenge.

The goal of this challenge is to identify fractured bone in limbs using CT scans. We offer a collection of 5567 clinically annotated anonymized CT-Scan Slices, obtained from multiple hospitals. This dataset includes a total of 24 CT scans, each containing approximately 200-300 slices. The scans cover both the upper and lower limbs. To participate and know more about the competition please register through this link. You will get an invite link for a Kaggle competition after you register. Important note. Winners will receive conference registration fees and will be invited to present their papers during the conference. In addition, papers will be selected for a possible publicaiton in a journal issue (SCI indexed). Competition deadline: 10/15/2023 11:59 PM (UTC)

Paper submission

Papers are expected to be within the 8-15 page range. The review process takes into account both the quality in writing and the scientific impact of the work. Authors should clearly identify the problem, their contribution(s), justification with respect to the state-of-the-art works. The program committee would like to review those, who develop, argue, and provide results. We recommend using the LaTeX template for preparing submissions. Please follow the template for preparing a conference paper CCIS, Springer Nature and Overleaf . Submissions should be made through the RTIP2R 2023 Microsoft CMT webpage: https://cmt3.research.microsoft.com/RTIP2R2023

Outstanding PhD dissertation award

Submit your nominations to [email protected] and [email protected] with the subject line RTIP2R2023: Best PhD Dissertation Award Nomination. The submission deadline is July 31, 2023 (all time zones). Please check this file for further details: Download the pdf .

General chairs

KC Santosh, PAMI - Computer Science, University of South Dakota Ayush Goyal, Texas A&M University - Kingsville

digital image processing Recently Published Documents

Total documents.

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Developing Digital Photomicroscopy

(1) The need for efficient ways of recording and presenting multicolour immunohistochemistry images in a pioneering laboratory developing new techniques motivated a move away from photography to electronic and ultimately digital photomicroscopy. (2) Initially broadcast quality analogue cameras were used in the absence of practical digital cameras. This allowed the development of digital image processing, storage and presentation. (3) As early adopters of digital cameras, their advantages and limitations were recognised in implementation. (4) The adoption of immunofluorescence for multiprobe detection prompted further developments, particularly a critical approach to probe colocalization. (5) Subsequently, whole-slide scanning was implemented, greatly enhancing histology for diagnosis, research and teaching.

Parallel Algorithm of Digital Image Processing Based on GPU

Quantitative identification cracks of heritage rock based on digital image technology.

Abstract Digital image processing technologies are used to extract and evaluate the cracks of heritage rock in this paper. Firstly, the image needs to go through a series of image preprocessing operations such as graying, enhancement, filtering and binaryzation to filter out a large part of the noise. Then, in order to achieve the requirements of accurately extracting the crack area, the image is again divided into the crack area and morphological filtering. After evaluation, the obtained fracture area can provide data support for the restoration and protection of heritage rock. In this paper, the cracks of heritage rock are extracted in three different locations.The results show that the three groups of rock fractures have different effects on the rocks, but they all need to be repaired to maintain the appearance of the heritage rock.

Determination of Optical Rotation Based on Liquid Crystal Polymer Vortex Retarder and Digital Image Processing

Discussion on curriculum reform of digital image processing under the certification of engineering education, influence and application of digital image processing technology on oil painting creation in the era of big data, geometric correction analysis of highly distortion of near equatorial satellite images using remote sensing and digital image processing techniques, color enhancement of low illumination garden landscape images.

The unfavorable shooting environment severely hinders the acquisition of actual landscape information in garden landscape design. Low quality, low illumination garden landscape images (GLIs) can be enhanced through advanced digital image processing. However, the current color enhancement models have poor applicability. When the environment changes, these models are easy to lose image details, and perform with a low robustness. Therefore, this paper tries to enhance the color of low illumination GLIs. Specifically, the color restoration of GLIs was realized based on modified dynamic threshold. After color correction, the low illumination GLI were restored and enhanced by a self-designed convolutional neural network (CNN). In this way, the authors achieved ideal effects of color restoration and clarity enhancement, while solving the difficulty of manual feature design in landscape design renderings. Finally, experiments were carried out to verify the feasibility and effectiveness of the proposed image color enhancement approach.

Discovery of EDA-Complex Photocatalyzed Reactions Using Multidimensional Image Processing: Iminophosphorane Synthesis as a Case Study

Abstract Herein, we report a multidimensional screening strategy for the discovery of EDA-complex photocatalyzed reactions using only photographic devices (webcam, cellphone) and TLC analysis. An algorithm was designed to identify automatically EDA-complex reactive mixtures in solution from digital image processing in a 96-wells microplate and by TLC-analysis. The code highlights the region of absorption of the mixture in the visible spectrum, and the quantity of the color change through grayscale values. Furthermore, the code identifies automatically the blurs on the TLC plate and classifies the mixture as colorimetric reactions, non-reactive or potentially reactive EDA mixtures. This strategy allowed us to discover and then optimize a new EDA-mediated approach for obtaining iminophosphoranes in up to 90% yield.

Mangosteen Quality Grading for Export Markets Using Digital Image Processing Techniques

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9 th International Conference on Image Processing and Pattern Recognition (IPPR 2023)

June 24 ~ 25, 2023, copenhagen, denmark.

Due to the current COVID-19 pandemic, registered authors are now able to present their work through our online platforms New

Scope & Topics

9 th International Conference on Image Processing and Pattern Recognition (IPPR 2023) is a forum for presenting new advances and research results in the fields of Digital Image Processing. The Workshop will bring together leading researchers, engineers and scientists in the domain of interest from around the world. The scope of the journal covers all theoretical and practical aspects of the Digital Image Processing & Pattern Recognition, from basic research to development of application.

Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

Topics of interest include, but are not limited to, the following:

• Image Coding and Compression
• Face Recognition and Super-Resolution Imaging
• Image Segmentation
• Face Recognition
• 3-D and Surface Reconstruction
• 3D and Stereo Imaging
• Analog and Mixed Signal Processing
• Application and Others
• Applications (Biomedical, Bioinformatics, Genomic, Seismic, Radar, Sonar, Remote Sensing, Positioning, etc.)
• Array Signal Processing
• Audio/Speech Processing and Coding
• Digital and Mobile Signal Processing
• Statistical and Optical Signal Processing
• Data Mining Techniques
• Motion Detection
• Content-based Image Retrieval
• Video Signal Processing
• Watermarking
• Detection and Estimation of Signal Parameters
• Signal Identification
• Nonlinear Signals and Systems
• Time-Frequency Signal Analysis
• Signal Reconstruction
• Spectral Analysis
• Filter Design and Structures
• FIR, IIR and Adaptive Filters
• Signal Noise Control
• Multiple Filtering and Filter Banks
• Biomedical Imaging Technologies
• Biometrics and Pattern Recognition
• Cognitive and Biologically-Inspired Vision
• Color and Texture
• Communication Signal processing
• Computer Vision & VR
• Constraint processing Computer
• Communication and Networks
• Internet Signal Processing
• Knowledge Representation and High-Level Vision
• Medical Image Analysis
• Motion and Tracking Stereo and Structure from Motion
• Multidimensional Signal Processing
• Multi-view Geometry
• Neural Networks and Genetic Algorithms
• Object Detection, Recognition and Categorization
• Pattern Recognition in New Modalities
• PDE for Image Processing
• Performance Evaluation
• Radar Signal Processing
• Remote Sensing
• Segmentation
• Sensor Array and Multi-channel Processing
• Shape Representation
• Signal Processing Education
• Sonar Signal Processing and Localization
• Speech, Audio and Music Processing
• Statistic Learning & Pattern Recognition
• Text processing
• Time-Frequency/Time-Scale Analysis
• Video Analysis and Event Recognition
• Video Compression & Streaming
• Video Surveillance and Monitoring
• Distributed Source Coding
• Document Recognition
• DSP Implementation and Embedded Systems
• Face and Gesture
• Hardware Implementation for Signal Processing
• Higher Order Spectral Analysis
• Illumination and Reflectance Modeling
• Image and Video Retrieval
• Image Processing & Understanding Image-Based Modeling

Paper Submission

Authors are invited to submit papers through the conference Submission System by February 18, 2023 .

Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from IPPR 2023 , after further revisions, will be published in the special issues of the following journals

• Signal & Image Processing : An International Journal (SIPIJ) - WJCI Indexed
• International Journal of VLSI Design & Communication Systems (VLSICS)
• International Journal of Embedded Systems and Applications (IJESA)
• International Journal on Organic Electronics (IJOE)
• Information Technology in Industry (ITII)

Important Dates

Submission Deadline : February 18, 2023

Authors Notification : March 10, 2023

Registration & Camera-Ready Paper Due : March 18, 2023

Invited Talk

Supported by, other conferences, proceedings.

Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC Digital Library

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Top 5 papers.

Copyright © IPPR 2023

Research Topics

Biomedical Imaging

The current plethora of imaging technologies such as magnetic resonance imaging (MR), computed tomography (CT), position emission tomography (PET), optical coherence tomography (OCT), and ultrasound provide great insight into the different anatomical and functional processes of the human body.

Computer Vision

Computer vision is the science and technology of teaching a computer to interpret images and video as well as a typical human. Technically, computer vision encompasses the fields of image/video processing, pattern recognition, biological vision, artificial intelligence, augmented reality, mathematical modeling, statistics, probability, optimization, 2D sensors, and photography.

Image Segmentation/Classification

Extracting information from a digital image often depends on first identifying desired objects or breaking down the image into homogenous regions (a process called 'segmentation') and then assigning these objects to particular classes (a process called 'classification'). This is a fundamental part of computer vision, combining image processing and pattern recognition techniques.

Multiresolution   Techniques

The VIP lab has a particularly extensive history with multiresolution methods, and a significant number of research students have explored this theme. Multiresolution methods are very broad, essentially meaning than an image or video is modeled, represented, or features extracted on more than one scale, somehow allowing both local and non-local phenomena.

Remote Sensing

Remote sensing, or the science of capturing data of the earth from airplanes or satellites, enables regular monitoring of land, ocean, and atmosphere expanses, representing data that cannot be captured using any other means. A vast amount of information is generated by remote sensing platforms and there is an obvious need to analyze the data accurately and efficiently.

Scientific Imaging

Scientific Imaging refers to working on two- or three-dimensional imagery taken for a scientific purpose, in most cases acquired either through a microscope or remotely-sensed images taken at a distance.

Stochastic Models

In many image processing, computer vision, and pattern recognition applications, there is often a large degree of uncertainty associated with factors such as the appearance of the underlying scene within the acquired data, the location and trajectory of the object of interest, the physical appearance (e.g., size, shape, color, etc.) of the objects being detected, etc.

Video Analysis

Video analysis is a field within  computer vision  that involves the automatic interpretation of digital video using computer algorithms. Although humans are readily able to interpret digital video, developing algorithms for the computer to perform the same task has been highly evasive and is now an active research field.

Evolutionary Deep Intelligence

Deep learning has shown considerable promise in recent years, producing tremendous results and significantly improving the accuracy of a variety of challenging problems when compared to other machine learning methods.

Discovery Radiomics

Radiomics, which involves the high-throughput extraction and analysis of a large amount of quantitative features from medical imaging data to characterize tumor phenotype in a quantitative manner, is ushering in a new era of imaging-driven quantitative personalized cancer decision support and management. 

Sports Analytics

Sports Analytics is a growing field in computer vision that analyzes visual cues from images to provide statistical data on players, teams, and games. Want to know how a player's technique improves the quality of the team? Can a team, based on their defensive position, increase their chances to the finals? These are a few out of a plethora of questions that are answered in sports analytics.

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Graph Embedding Interclass Relation-Aware Adaptive Network for Cross-Scene Classification of Multisource Remote Sensing Data

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AI-Driven Digital Image Processing: Latest Advances and Prospects

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section " Computer Science & Engineering ".

Deadline for manuscript submissions: 15 December 2024 | Viewed by 626

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Dear Colleagues,

Digital Image Processing significantly impacts our ability to handle visual information and has become crucial in the development of technology across varied fields. This area's recent progress is mainly fueled by advancements in artificial intelligence (AI), especially deep learning, driving a shift towards more intelligent image processing systems. These AI-driven systems have improved applications in autonomous vehicles, medical diagnostics, remote sensing and space exploration by enabling sophisticated image analysis for decision-making and research.

The emergence of deep learning has introduced efficient methods that accurately handle complex datasets, supporting better data interpretation. AI integration with image processing enhances our capabilities in various sectors, from environmental monitoring to improving vehicle perception systems and medical diagnostic accuracy.

However, the rise of AI in image processing brings challenges, such as managing large data volumes, ensuring model reliability, and addressing privacy and bias concerns. These issues highlight the need for continuous innovation and a collaborative platform for sharing the latest developments in Digital Image Processing.

To address these needs, the "AI-Driven Digital Image Processing: Latest Advances and Prospects" Special Issue aims to gather and disseminate recent advancements, methodologies, and ideas in the field, with the hope of promoting collaboration among experts to overcome current challenges.

Articles and reviews on image processing are welcome. The specific topics to be addressed include, but are not limited to, the following:

• Semantic segmentation and instance segmentation;
• UAV/UAS/BEV/Satellite 3D reconstruction and semantic perception;
• Multimodal Large Models;
• Multimodal data collaborative analysis and processing;
• Video processing;
• Image processing for Medical Imaging and Deep Space Exploration;
• Benchmark datasets for image processing and large models;
• Semi-/Self-supervised image analysis;
• Few-shot/Zero-shot image processing;
• Image-processing-based applications;
• Multi-source sensing data for urban analytics.

Dr. Guanzhou Chen Dr. Kun Zhu Dr. Jinzhou Cao Guest Editors

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website . Once you are registered, click here to go to the submission form . Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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M.Tech/Ph.D Thesis Help in Chandigarh | Thesis Guidance in Chandigarh

[email protected]

+91-9465330425

What is Digital Image Processing?

Digital image processing is the process of using computer algorithms to perform image processing on digital images. Latest topics in digital image processing for research and thesis are based on these algorithms. Being a subcategory of digital signal processing, digital image processing is better and carries many advantages over analog image processing. It permits to apply multiple algorithms to the input data and does not cause the problems such as the build-up of noise and signal distortion while processing. As images are defined over two or more dimensions that make digital image processing “a model of multidimensional systems”. The history of digital image processing dates back to early 1920s when the first application of digital image processing came into news. Many students are going for this field for their  m tech thesis  as well as for Ph.D. thesis. There are various thesis topics in digital image processing for M.Tech, M.Phil and Ph.D. students. The list of thesis topics in image processing is listed here. Before going into  topics in image processing , you should have some basic knowledge of image processing.

Latest research topics in image processing for research scholars:

• The hybrid classification scheme for plant disease detection in image processing
• The edge detection scheme in image processing using ant and bee colony optimization
• To improve PNLM filtering scheme to denoise MRI images
• The classification method for the brain tumor detection
• The CNN approach for the lung cancer detection in image processing
• The neural network method for the diabetic retinopathy detection
• The copy-move forgery detection approach using textual feature extraction method
• Design face spoof detection method based on eigen feature extraction and classification
• The classification and segmentation method for the number plate detection
• Find the link at the end to download the latest thesis and research topics in Digital Image Processing

Formation of Digital Images

Firstly, the image is captured by a camera using sunlight as the source of energy. For the acquisition of the image, a sensor array is used. These sensors sense the amount of light reflected by the object when light falls on that object. A continuous voltage signal is generated when the data is being sensed. The data collected is converted into a digital format to create digital images. For this process, sampling and quantization methods are applied. This will create a 2-dimensional array of numbers which will be a digital image.

Why is Image Processing Required?

• Image Processing serves the following main purpose:
• Visualization of the hidden objects in the image.
• Enhancement of the image through sharpening and restoration.
• Seek valuable information from the images.
• Measuring different patterns of objects in the image.
• Distinguishing different objects in the image.

Applications of Digital Image Processing

• There are various applications of digital image processing which can also be a good topic for the thesis in image processing. Following are the main applications of image processing:
• Image Processing is used to enhance the image quality through techniques like image sharpening and restoration. The images can be altered to achieve the desired results.
• Digital Image Processing finds its application in the medical field for gamma-ray imaging, PET Scan, X-ray imaging, UV imaging.
• It is used for transmission and encoding.
• It is used in color processing in which processing of colored images is done using different color spaces.
• Image Processing finds its application in machine learning for pattern recognition.

List of topics in image processing for thesis and research

• There are various in digital image processing for thesis and research. Here is the list of latest thesis and research topics in digital image processing:
• Image Acquisition
• Image Enhancement
• Image Restoration
• Color Image Processing
• Wavelets and Multi Resolution Processing
• Compression
• Morphological Processing
• Segmentation
• Representation and Description
• Object recognition
• Knowledge Base

1. Image Acquisition:

Image Acquisition is the first and important step of the digital image of processing . Its style is very simple just like being given an image which is already in digital form and it involves preprocessing such as scaling etc. It starts with the capturing of an image by the sensor (such as a monochrome or color TV camera) and digitized. In case, the output of the camera or sensor is not in digital form then an analog-to-digital converter (ADC) digitizes it. If the image is not properly acquired, then you will not be able to achieve tasks that you want to. Customized hardware is used for advanced image acquisition techniques and methods. 3D image acquisition is one such advanced method image acquisition method. Students can go for this method for their master’s thesis and research.

2. Image Enhancement:

Image enhancement is one of the easiest and the most important areas of digital image processing. The core idea behind image enhancement is to find out information that is obscured or to highlight specific features according to the requirements of an image. Such as changing brightness & contrast etc. Basically, it involves manipulation of an image to get the desired image than original for specific applications. Many algorithms have been designed for the purpose of image enhancement in image processing to change an image’s contrast, brightness, and various other such things. Image Enhancement aims to change the human perception of the images. Image Enhancement techniques are of two types: Spatial domain and Frequency domain.

3. Image Restoration:

Image restoration involves improving the appearance of an image. In comparison to image enhancement which is subjective, image restoration is completely objective which makes the sense that restoration techniques are based on probabilistic or mathematical models of image degradation. Image restoration removes any form of a blur, noise from images to produce a clean and original image. It can be a good choice for the M.Tech thesis on image processing. The image information lost during blurring is restored through a reversal process. This process is different from the image enhancement method. Deconvolution technique is used and is performed in the frequency domain. The main defects that degrade an image are restored here.

4. Color Image Processing:

Color image processing has been proved to be of great interest because of the significant increase in the use of digital images on the Internet. It includes color modeling and processing in a digital domain etc. There are various color models which are used to specify a color using a 3D coordinate system. These models are RGB Model, CMY Model, HSI Model, YIQ Model. The color image processing is done as humans can perceive thousands of colors. There are two areas of color image processing full-color processing and pseudo color processing. In full-color processing, the image is processed in full colors while in pseudo color processing the grayscale images are converted to colored images. It is an interesting topic in image processing.

IEEE 2024-2025 : IMAGE PROCESSING Projects

Click here matlab image processing projects, click here  python  ieee image processing projects .

For Outstation Students, we are having online project classes both technical and coding using net-meeting software

For details, call: 9886692401/9845166723.

DHS Informatics  providing  latest 2024-2025 IEEE projects  on Image Processing for the final year engineering students. DHS Informatics trains all students to develop their project with good idea what they need to submit in college to get good marks. DHS Informatics offers placement training in Bangalore and the program name is  OJT  –  On Job Training , job seekers as well as final year college students can join in this placement training program and job opportunities in their dream IT companies. We are providing IEEE projects for BE / B.TECH, M.TECH, MCA, BCA, DIPLOMA students from more than two decades.

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• Python 2024 – 2025 IEEE PYTHON PROJECTS CSE | ECE | ISE
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Image processing

Efficient quantum information hiding for remote medical image sharing.

Abstract : Information hiding aims to embed secret data into the multimedia, such as image, audio, video,  and text. In this paper, two new quantum information hiding approaches are put forward. A  quantum stenography approach is proposed to hide a quantum secret image into a quantum  cover image. The quantum secret image is encrypted first using a controlled-NOT gate to  demonstrate the security of the embedded data. The encrypted secret image is embedded into the  quantum cover image using the two most and least significant qubits. In addition, a quantum  image watermarking approach is presented to hide a quantum watermark gray image into a  quantum carrier image. The quantum watermark image, which is scrambled by utilizing Arnold’s  cat map, is then embedded into the quantum carrier image using the two least and most  significant qubits. Only the watermarked image and the key are sufficient to extract the  embedded quantum watermark image. The proposed novelty has been illustrated using a scenario  of sharing medical imagery between two remote hospitals. The simulation and analysis  demonstrate that the two newly proposed approaches have excellent visual quality and high  embedding capacity y and security.                                                                                                                                                                                                                                                                                                                      

An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images

Abstract : Reversible data hiding in encrypted images (RDHEI) is an effective technique to embed data in the encrypted domain. An original image is encrypted with a secret key and during or after its transmission, it is possible to embed additional information in the encrypted image, without knowing the encryption key or the original content of the image. During the decoding process, the secret message can be extracted and the original image can be reconstructed. In the last few years, RDHEI has started to draw research interest. Indeed, with the development of cloud computing, data privacy has become a real issue. However, none of the existing methods allows us to hide a large amount of information in a reversible manner. In this paper, we propose a new reversible method based on MSB (most significant bit) prediction with a very high capacity. We present two approaches, these are: high capacity reversible data hiding approach with correction of prediction errors (CPE-HCRDH) and high capacity reversible data hiding approach with embedded prediction errors (EPE-HCRDH). With this method, regardless of the approach used, our results are better than those  obtained with current state of the art methods, both in terms of reconstructed image quality and embedding capacity                                                                                                                                                                                                                                                            

Visual Secret Sharing Schemes Encrypting Multiple Images

Abstract : The aim of this paper is to maximize the range of the access control of visual secret sharing (VSS) schemes encrypting multiple images. First, the formulation of access structures for a single secret is generalized to that for multiple secrets. This generalization is maximal in the sense that the generalized for-mulation makes no restrictions on access structures; in particular, it includes the existing ones as special cases. Next, a sufficient condition to be satisfied by the encryption of VSS schemes realizing an access structure for multiple secrets of the most general form is introduced, and two constructions of VSS schemes with encryption satisfying this condition are provided. Each of the two constructions has its advantage against the other; one is more general and can generate VSS schemes with strictly better contrast and pixel expansion than the other, while the other has a straightforward implementation. Moreover, for threshold access structures, the pixel expansions of VSS schemes generated by the  latter construction are estimated and turn out to be the same as those of the existing schemes called the threshold multiple-secret visual cryptographic schemes. Finally, the optimality of the former construction is examined, giving that there exist access structures for which it generates no optimal VSS schemes.                                                                                                                                                                               

Computer Assisted Segmentation of Palmprint Images for Biometric Research

Abstract : One of the becoming popular bio metric modalities   is the palm print. This bio metric modality is rich with   information, such as minutiae, ridges, wrinkles, and creases.   This research team is interested to investigate the creases for   bio metric identification. The palm print images in this research   have been captured by using a commercially available consumer   scanner. For each palm print image, two square regions on the   palm print image are extracted for bio metric identification   purpose. One of the regions is from the hyperthyroid region,   while the another is from the inter digital region. Due to   misalignment of the hand, the process of extraction of these   regions is tedious and time-consuming. Therefore, in this paper,   a computer-aided method has been proposed to simplify the   extraction process. The user only needs to mark two points on   the palm print image. Based on these points, the palm print image   will be aligned, and those two regions are extracted   automatically.                                                                                                                                                                                     

Image Classification using Manifold Learning Based Non-Linear Dimensionality Reduction

Abstract : This paper presents fast categorization or  classification of images on an animal data set using different  classification algorithm in combination with manifold learning  algorithms. The paper will focus on comparing the effects of  different non-linear dimensional reduction algorithms on  speed and accuracy of different classification algorithms. It  examines how manifold learning algorithms can improve  classification speed by reducing the number of features in the  vector representation of images while keeping the classification  accuracy high.                                                                                                                                 

IEEE IMAGE PROCESSING PROJECTS (2024-2025)

DHS Informatics believes in students’ stratification, we first brief the students about the technologies and type of Image Processing projects and other domain projects. After complete concept explanation of the IEEE Image Processing projects, students are allowed to choose more than one IEEE Image Processing projects for functionality details. Even students can pick one project topic from Image Processing and another two from other domains like Image Processing, data mining, image process, information forensic, big data, Image Processing, Image Processing, data science, block chain etc. DHS Informatics is a pioneer institute in Bangalore / Bengaluru; we are supporting project works for other institute all over India. We are the leading final year project centre in Bangalore / Bengaluru and having office in five different main locations Jayanagar, Yelahanka, Vijayanagar, RT Nagar & Indiranagar.

We allow the ECE, CSE, ISE final year students to use the lab and assist them in project development work; even we encourage students to get their own idea to develop their final year projects for their college submission.

DHS Informatics first train students on project related topics then students are entering into practical sessions. We have well equipped lab set-up, experienced faculties those who are working in our client projects and friendly student coordinator to assist the students in their college project works.

We appreciated by students for our Latest IEEE projects & concepts on final year Image Processing projects for ECE , CSE , and ISE departments.

Latest IEEE 2024-2025 projects on Image Processing with real time concepts which are implemented using Java , MATLAB , and NS2 with innovative ideas. Final year students of computer Image Processing, computer science, information science, electronics and communication can contact our corporate office located at Jayanagar, Bangalore for Image Processing project details.

IMAGE PROCESSING

Image processing  is processing of images using mathematical operations by using any form of signal processing for which the input is an image, a series of images, such as a photograph, the output of image processing may be either an image or a set of characteristics or parameters related to the image. Most image-processing techniques involve isolating the individual color planes of an image and treating them as two-dimensional signal and applying standard signal-processing techniques to them. Images are also processed as three-dimensional signals with the third dimension being time or the z-axis.

Image processing usually refers to digital image processing, but optical and analog image processing also are possible. This article is about general techniques that apply to all of them. The acquisition of images (producing the input image in the first place) is referred to as imaging.

Java Final year CSE projects in Bangalore

• Java Information Forensic / Block Chain B.E Projects
• Java  Cloud Computing B.E Projects
• Java  Big Data with Hadoop B.E Projects
• Java  Networking & Network Security B.E Pr ojects
• Java  Data Mining / Web Mining / Cyber Secu rity B.E Projects
• Java DataScience / Machine Learning  B.E Projects
•  Java Artificaial Inteligence B.E Projects
• Java  Wireless Sensor Network B.E Projects
• Java  Distributed & Parallel Networking B.E Projects
• Java Mobile Computing B.E Projects

Android Final year CSE projects in Bangalore

• Android  GPS, GSM, Bluetooth & GPRS B.E Projects
• Android  Embedded System Application Projetcs for B.E
• Android  Database Applications Projects for B.E Students
• Android  Cloud Computing Projects for Final Year B.E Students
• Android  Surveillance Applications B.E Projects
• Android  Medical Applications Projects for B.E

Embedded  Final year CSE projects in Bangalore

• Embedded  Robotics Projects for M.tech Final Year Students
• Embedded  IEEE Internet of Things Projects for B.E Students
• Embedded   Raspberry PI Projects for B.E Final Year Students
• Embedded  Automotive Projects for Final Year B.E Students
• Embedded  Biomedical Projects for B.E Final Year Students
• Embedded  Biometric Projects for B.E Final Year Students
• Embedded  Security Projects for B.E Final Year

MatLab  Final year CSE projects in Bangalore

• Matlab  Image Processing Projects for B.E Students
• MatLab  Wireless Communication B.E Projects
• MatLab  Communication Systems B.E Projects
• MatLab  Power Electronics Projects for B.E Students
• MatLab  Signal Processing Projects for B.E
• MatLab  Geo Science & Remote Sensors B.E Projects
• MatLab  Biomedical Projects for B.E Students

• Jordan University of Science and Technology

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'I gave birth to triplets and it pushed me to the brink of bankruptcy'

New research "lays bare the grim reality facing families with multiples", including the financial burden, mental health toll and lack of support, a charity warns. Sky News spoke to parents of triplets and twins to hear the challenges they face.

Social affairs and health reporter @megbaynes

Wednesday 11 September 2024 19:04, UK

When Monique Bertrand found out she was carrying triplets at eight weeks pregnant, she had no idea the unexpected arrivals would push her family to the brink of bankruptcy.

New research has found families with twins or triplets face at least a £20,000 financial hit in the first year after birth, compared with those who have two babies in succession.

Having been told she could never carry children, Monique had been considering foster care when she unexpectedly fell pregnant - but a bigger surprise was in store when she found out she had naturally conceived triplets.

After a difficult pregnancy, at 31 weeks and surrounded by a team of 35 doctors, nurses and midwives, she gave birth to Macho and Lylah, weighing a tiny 2lb 8oz, and Trinity, weighing just 2lb 1oz.

Research, commissioned by the charity Twins Trust and carried out by Per Capita, found raising multiples is more difficult in the UK than in almost any other advanced OECD economy, due to the lack of additional support.

"Triplet mums just need extra hands," said Monique, 39, from Lewisham, southeast London.

The triplets spent 50 days in the hospital (Monique herself was admitted for 34 days) and by the time they returned home, her partner had already used up his two weeks of paternity leave. With him working lengthy night shifts, she was left to care for three infants alone.

"I felt I could not do it. I felt I wanted to run away. There was no support in any way," she said.

"I wish the government realised there is a huge difference between having multiples and having singletons."

Families of twins and triplets experience a 15% decline in household income (around £12,500), with 72% having to buy a new car to accommodate their children, according to the research. Twins and triplets are often born premature, requiring families to take more time off work to care for their children.

"People don't realise, I have to pay for everything three times," said Monique, who works as an assistant director of education. "A £20 baby outfit, for me that costs £60. We go through nappies like they are tap water, formula... the costs just mount up.

"There is no passing things down between children, you have to have everything at once. It almost bankrupted us."

She said she knew of some multiple mums who had to give cow's milk to their children early, simply because they could not afford the cost of formula.

Families she had previously supported would send Monique clothes, food, formula and baby items to help the family survive.

"The doorbell would ring, and it would be Amazon delivering three high chairs," she said.

'I had to work while my twins were in hospital'

When Frank Fallon and Frankie Wakefield's twins, Ezra and Theo, arrived a day before their wedding, it was just the latest surprise of an unexpected pregnancy.

The couple had gone through IVF but only implanted one embryo, to try to mitigate the risk of multiples - but their eight-week scan showed two healthy heartbeats.

Born three months early, Frank had to continue working while the twins spent seven weeks in hospital, to avoid using up all his paternity leave.

"I would go visit them at 6am before work and we had to rely on friends and family to drive Frankie to hospital to see them," he said.

Now the twins are energetic two-year-olds, and the couple are finally having their much-delayed wedding on Saturday, but they are calling for more support for multiple families.

"Everything just adds up," said Frank. "Extra nappies [the family orders approximately 240 every four to six weeks], high energy bills because they are having more baths.

"I think I am at Tesco every day because they now go through litres of milk."

He added: "Even children's classes that Frankie goes to so she can socialise, you have to pay double for the extra baby."

'Childcare would have cost £5k a month'

Almost 90% of the 1,800 families surveyed said current childcare provisions are inadequate.

As Monique prepared to return to work, she sat down and wrote her resignation letter, after realising the cost of childcare for her triplets would be more than £5,000 a month.

"It broke my heart because I have never not worked," she said.

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On learning this, her family held a meeting, volunteering to look after the children on different days so she could return to work. Now the twins are 21 months old, she qualifies for 15 hours free childcare, but the bill still stands at £3,500 a month, and she relies heavily on her family to help.

At one point, Frank considered putting his children in on different days, to try and lower the cost of their £4,000 a month childcare bill.

"We are lucky we have both been promoted, but in our old jobs we would never have been able to afford it," he said.

The Twins Trust report is calling for maternity pay to be allocated per baby, rather than per pregnancy, as well as an expansion of the Sure Start Maternity Grant and additional mental health support for families of multiples.

Shauna Leven, chief executive of Twins Trust, said: "This report lays bare the grim reality facing families with multiples - the financial burden, mental health toll and lack of support.

"Raising multiples is harder in the UK than almost any other nation. We will continue to campaign tirelessly to tackle the issues highlighted here, so our families can access the support they desperately need and deserve.

"With one set of multiples born every hour across the UK, it's critical that our society steps up and provides adequate support, rather than sending our families to the back of the queue."

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• Frontiers in Nutrition
• Food Chemistry
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The effects of innovative food processing technologies on the bioactive components in food

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Human nutrition is profoundly influenced by the quality and composition of the foods we consume, particularly the presence of bioactive components—compounds that offer health benefits beyond basic nutrition. Recent advancements in food processing technologies have opened new avenues for enhancing or preserving these bioactive components, such as vitamins, polyphenols, and antioxidants, which are sensitive to traditional processing methods. Innovative techniques like high-pressure processing, pulsed electric fields, and cold plasma represent a new era in food processing. These methods are designed to minimize the degradation of bioactive compounds by avoiding the high temperatures and prolonged exposure times typical of conventional thermal processing. For instance, high-pressure processing inactivates harmful microorganisms while preserving heat-sensitive nutrients maintain the natural bioactive profile of foods. Moreover, these technologies can alter the structural properties of food matrices, enhancing the release and absorption of bioactive components in the human body. This improved bioavailability can significantly influence human health by maximizing the potential benefits of these compounds. As research in this field continues to evolve, the application of innovative food processing technologies promises to play a crucial role in optimizing the nutritional quality of food, thereby supporting better health outcomes in human nutrition. This Research Topic aims to explore the effects of innovative food processing technologies on bioactive components in food, focusing on how these technologies influence the retention, stability, and bioavailability of bioactive compounds, as well as their implications for human health. We aim to make the most of the unique nature of innovative food processing technologies and the richness of bioactive components to drive progress in food nutrition. In addition, we seek to understand how these technologies can be optimized to maximize the nutritional value of processed foods and to identify any potential trade-offs between food safety, shelf-life extension, and bioactive integrity. • Strategies for preserving bioactive compounds in food products through novel processing techniques • Assessing the nutritional and health benefits of processed foods: considerations for incorporating bioactive components • Physical properties and structure of food and how this relates to human nutrition • Interactions between bioactive compounds, gut and human health • Isolation and analysis of food bioactive components while considering nutritional aspects • Nutritional effects of bioactive components including bioavailability and kinetic • Systematic reviews about future trends and opportunities in the development of sustainable food processing methods

Keywords : novel processing technology, functional component, bioavailability, health benefits, sustainability

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