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17 results for “gray level co-occurrence matrix”
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Research ArticleOpen accessPhrase in the titleFeature Fusion Technique for Colour Texture Classification System Based on Gray Level Co-occurrence MatrixA. Suresh, K. L. ShunmuganathanIn this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM) and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first non … …Journal of Computer Science, Vol. 8, Issue 12 · 5 Jan 2013 · 6,615 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePERFORMANCE ANALYSIS OF GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURE FEATURES FOR GLAUCOMA DIAGNOSISSakthivel Karthikeyan, N. RengarajanGlaucoma is a multifactorial optic neuropathy disease characterized by elevated Intra Ocular Pressure (IOP). As the visual loss caused by the disease is irreversible, early detection is essential. Fundus images are used as input and it is preprocessed using histogram equalization. First order features from histogram and second order features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 24 Dec 2013 · 7,326 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleContent Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering AlgorithmsB. Ramamurthy, K. R. ChandranProblem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies … …Journal of Computer Science, Vol. 8, Issue 7 · 24 May 2012 · 7,448 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGray-Level Co-occurrence Matrix Bone Fracture DetectionHum Yan Chai, Lai Khin Wee, Tan Tian Swee et al.Problem statement: Currently doctors in orthopedic wards inspect the bone x-ray images according to their experience and knowledge in bone fracture analysis. Manual examination of x-rays has multitude drawbacks. The process is time-consuming and subjective. Approach: Since detection of fractures is an important orthopedics and radiologic problem and therefore a Computer Aided Detection(CAD) system should be developed to improve the … …American Journal of Applied Sciences, Vol. 8, Issue 1 · 31 Jan 2011 · 8,968 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePLANT RECOGNITION USING STEREO LEAF IMAGE USING GRAY-LEVEL CO-OCCURRENCE MATRIXHermawan Syahputra, Agus Harjoko, Retantyo Wardoyo, Reza PulunganAdequate knowledge, such as information about the unique characteristics of each plant, is necessary to identify plant. Researchers have made plant recognition based on leaf characteristics. The leaf image-based plant recognition in view of different angles is a new challenge. In this study, the research on the plant recognition was conducted based on leaf images resulted from 3D stereo camera. … …Journal of Computer Science, Vol. 10, Issue 4 · 24 Dec 2013 · 8,116 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDirect Sequence and Frequency Hopping Signals Classification Based on Co-Occurrence Matrix and Clustering TechniquesHaidy S. Fouad, Hend A. Elsayed, Shawkat K. GirgisSpread Spectrum techniques (SS) were first developed for military applications, but currently, they have commercial applications. SS provides secure communication and allows multiple accesses for same radio spectrum. So, most Wireless Local Area Network (WLAN) systems use it, as do Cognitive Radios (CR), space systems and Global Positioning Systems (GPS). Direct Sequence Spread Spectrum (DSSS) and frequency hopped spread spectrum … …Journal of Computer Science, Vol. 15, Issue 1 · 10 Jan 2019 · 8,203 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPREDICTION OF GLIOMA USING GENETIC OPTIMIZED NEURAL NETWORKS. Karpagam, S. GowriNeural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Glioma by creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this study proposed a … …Journal of Computer Science, Vol. 9, Issue 11 · 1 Oct 2013 · 6,693 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPalmprint Recognition using Feature Level FusionR. Gayathri, P. RamamoorthyProblem statement: Palmprint based biometric method has gained high impact over the other biometric methods due to its ease of acquisition, reliability and high client acceptance. Multiple feature extraction from image gives higher accuracy of the authentication system. Approach: This study presents the palmprint based identification methodology which uses the Gabor wavelet entropy to extract multiple features existing on the … …Journal of Computer Science, Vol. 8, Issue 7 · 19 May 2012 · 6,982 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Feature Selection for Kidney Ultrasound Image Classification Using Binary Coati Weighted Mean Vector AlgorithmFizhan Kausar, Ramamurthy B.The analysis of medical images presents many challenges, especially when making precise diagnoses. In pediatric Chronic Kidney Disease (CKD), early identification is critical because of its gradual progression to significant kidney failure. This study proposes a diagnostic framework for pediatric ultrasound image classification that incorporated machine learning and advanced feature selection methods. This approach is divided into four stages: Preprocessing, … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,563 accessesView PDFCite