Research ArticleOpen accessEvery word in the titleCOMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUESD. Ramkumar, I. Jacob Raglend, K. BatriIn this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 17 Apr 2014 · 6,662 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNON-COOPERATIVE IRIS RECOGNITION: A NOVEL APPROACH FOR SEGMENTATION AND FAKE IDENTIFICATIONM. Rajeev Kumar, M. Dilsath Fathima, K. Kiruthika, M. S. SaravananIris recognition, the ability to recognize and distinguish individuals by their pattern, is the most reliable biometric in terms of recognition and identification performance. However, performance of these systems is affected by the heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstruction and reflection) when the cooperation is not expectable from the subject. Current Iris … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,744 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIdentification of Proliferative Diabetic Retinopathy Using Texture SegmentationG. Tamil Pavai, S. Tamil SelviIn this study, it is proposed fast texture segmentation of detection of proliferative diabetic retinopathy. proliferative diabetic retinopathy is characterized by the revascularization on the optic disc or on the retinal area or both, as a result of diabetes mellitus. It may leads to the blindness if it is not detected and treated in proper time. This study proposes a … …Journal of Computer Science, Vol. 9, Issue 3 · 26 Apr 2013 · 6,319 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA 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 accessEvery word in the titleDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleVideo Retrieval using Histogram and Sift Combined with Graph-based Image SegmentationTran Quang Anh, Pham Bao, Tran Thuong Khanh et al.Problem statement: Content-Based Video Retrieval (CBVR) is still an open hard problem because of the semantic gap between low-level features and high-level features, largeness of database, keyframe’s content, choosing feature.In this study we introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Conclusion/Recommendations: Our algorithm is built … …Journal of Computer Science, Vol. 8, Issue 6 · 15 Mar 2012 · 7,013 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSegmentation and Recognition of Handwritten Numeric ChainsSalim Ouchtati, Mouldi Bedda, Abderrazak LachouriAutomatic reading of numeric chains has been attempted in several application areas such as bank cheque processing, postal code recognition and form processing. Such applications have been very popular in handwriting recognition research, due to the possibility to reduce considerably the manual effort involved in these tasks. In this study we propose an off line system for the recognition of … …Journal of Computer Science, Vol. 3, Issue 4 · 30 Apr 2007 · 7,636 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery LocalizationAshutosh Pandey, Niranjan Lal, Ashish Kumar ChakravertiCopy-move forgery is a widely used forgery method in digital image forensics, which involves copying and pasting a part of an image into another part of the image to hide or duplicate the visual information. This makes it difficult to detect such manipulations, particularly when the regions are subjected to geometric and photometric transformations. A Frost Filter-Enhanced Encoder-Decoder U-Net is … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 457 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDFCite