Research ArticleOpen accessIn the abstractGraph Based Segmentation in Content Based Image RetrievalP. S. Suhasini, K. S.R. Krishna, I. V.M. KrishnaProblem statement: Traditional image retrieval systems are content based image retrieval systems which rely on low-level features for indexing and retrieval of images. CBIR systems fail to meet user expectations because of the gap between the low level features used by such systems and the high level perception of images by humans. To meet the requirement as a preprocessing step … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn the Application of Artificial Neural Networks in Analyzing and Classifying the Human ChromosomesIbrahiem M.M. El EmaryThis study aimed to represent an advanced software tool assists in analyzing and classifying the human chromosomes. Our new software handles both classifying and analyzing the medical image of human chromosomes according to the following steps: 1- we use the image processing utilities in Matlab to analyze the image; where we provide a new filter to remove the noise depending … …Journal of Computer Science, Vol. 2, Issue 1 · 31 Jan 2006 · 7,515 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 383 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEMSutarman, Mazlina Abdul Majid, Jasni Mohamad ZainSign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: … …Journal of Computer Science, Vol. 9, Issue 11 · 27 Sep 2013 · 8,691 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLICENSE PLATE LOCALIZATION USING GABOR FILTERS AND NEURAL NETWORKSSami Ktata, Faouzi Benzarti, Hamid AmiriVehicle License Plate Detection (LPD) is an important step for the vehicle plate recognition which can be used in the intelligent transport systems. Many methods have been proposed for the detection of license plates based on: Mathematical morphology, Discrete Wavelet Transform, Hough Transform and others. In general, an LPR system includes four main parts: Vehicle image acquisition, license plate detection, … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,977 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Vehicle License Plate Detection and Recognition SystemKhalid W. MagladProblem statement: Automatic vehicle license plate detection and recognition is a key technique in most of traffic related applications and is an active research topic in the image processing domain. Different methods, techniques and algorithms have been developed for license plate detection and recognitions. Approach: Due to the varying characteristics of the license plate from country to country like numbering … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 9,008 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Review on Recent Research and Implementation Methodologies on Medical Image SegmentationS. K. Somasundaram, P. AlliProblem statement: Image segmentation plays a very important role in digital imaging applications for classifying the anatomical structures and other Regions of Interest. Segmentation refers to the process of identifying and isolating the surface and regions of the digital image which corresponds to the structural units. Approach: In the past few decades, many methods have been proposed to segment the … …Journal of Computer Science, Vol. 8, Issue 1 · 4 Nov 2011 · 7,117 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite