Results 11 to 20 of about 16,583,366 (283)
Intrusion Detection Based on Gray-Level Co-Occurrence Matrix and 2D Dispersion Entropy [PDF]
Applied Sciences, 2021 The Intrusion Detection System (IDS) is an important tool to mitigate cybersecurity threats in an Information and Communication Technology (ICT) infrastructure.
Gianmarco Baldini +2 more
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Gray level co-occurrence matrix and Schmitt neural network for Covid-19 diagnosis [PDF]
EAI Endorsed Transactions on e-Learning, 2021 INTRODUCTION: When COVID-19 spreads to most of the world, chest CT imaging is widely regarded as a convenient and feasible method for the diagnosis of suspected patients. In the traditional diagnosis method, doctors and experts judge these CT images and
Pengpeng Pi
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Identification of Anthracnose Disease in Mango Plant Using Clustering and Gray level Co- occurrence Matrix [PDF]
ITM Web of Conferences, 2020 The aim of this paper is to help farmers to identify disease without observing each and every mango plant by eyes. Farmers can use the pesticides according to the leaf disease identified.
Gawand Mamata +4 more
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Gray level co-occurrence matrix in polar orientation
, 2018 Classification of gray images based on their textural features is one of the main tools in medical image processing. Gray Level Co-occurrence Matrix (GLCM) is such a widely used technique which represents how frequently the different gray level combinations occur in an image, traditionally in Cartesian directions.
Bandara, Muditha S, Wansapura, Janaka
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Gray Level Co-Occurrence Matrix Computation Based On Haar Wavelet
Computer Graphics, Imaging and Visualisation (CGIV 2007), 2007 In this paper, a new computation for gray level co-occurrence matrix (GLCM) is proposed. The aim is to reduce the computation burden of the original GLCM computation. The proposed computation will be based on Haar wavelet transform. Haar wavelet transform is chosen because the resulting wavelet bands are strongly correlated with the orientation ...
M. M. Mokji, S. A. R. Abu-Bakar
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Jurnal Teknologi dan Sistem Komputer, 2018 Bamboo species can be identified from the bamboo leaf images. This study conducted the identification of bamboo species based on leaf texture using Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM) for texture feature ...
Endina Putri Purwandari +2 more
doaj +2 more sources
Computers in Biology and Medicine, 2016 The objective of the study was to evaluate whether texture analysis using histogram and gray level co-occurrence matrix (GLCM) parameters can help clinicians diagnose lymphocytic thyroiditis (LT) and differentiate LT according to pathologic grade. The background thyroid pathology of 441 patients was classified into no evidence of LT, chronic LT (CLT ...
Young Gyung Shin +9 more
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Ship Classification Based On Co-Occurrence Matrix and Support Vector Machines [PDF]
ElectricaSynthetic aperture radar (SAR) is an important and efficient imaging technology. This system provides robust information for various applications such as ship detection, climate change, and agricultural land modeling.
Kazım Hanbay, Taha Burak Özdemir
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Gray-Level Co-occurrence Matrix Bone Fracture Detection [PDF]
American Journal of Applied Sciences, 2011 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.
Hum, Yan Chai +5 more
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Analysis of GLCM Parameters for Textures Classification on UMD Database Images [PDF]
, 2015 Texture analysis is one of the most important techniques that have been used in image processing for many purposes, including image classification. The texture determines the region of a given gray level image, and reflects its relevant information ...
Lu, Joan, Mohamed, Alsadegh Saleh Saied
core +3 more sources