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Image Texture Analysis Based on Gray Level Co-Occurrence Matrix
2023 13th International Conference on Information Technology in Medicine and Education (ITME), 2023This paper studies the algorithm of Gray Level Co-occurrence Matrix (GLCM), explains the concrete meaning of 14 texture features based on GLCM, and points out the redundancy among texture features.
Chen Meilong +3 more
openaire +2 more sources
Ecological Indicators, 2020
Characterizing landscape patterns is an important analytical step towards understanding the effects of physical layouts on ecological and social processes.
Yujin Park, J. Guldmann
semanticscholar +3 more sources
Characterizing landscape patterns is an important analytical step towards understanding the effects of physical layouts on ecological and social processes.
Yujin Park, J. Guldmann
semanticscholar +3 more sources
Particulate matter characterization by gray level co-occurrence matrix based support vector machines
Journal of Hazardous Materials, 2012An efficient and highly reliable automatic selection of optimal segmentation algorithm for characterizing particulate matter is presented in this paper. Support vector machines (SVMs) are used as a new self-regulating classifier trained by gray level co-occurrence matrix (GLCM) of the image.
K, Manivannan +5 more
openaire +4 more sources
Biocybernetics and Biomedical Engineering, 2019
Epilepsy is a brain disorder that many persons of different ages in the world suffer from it. According to the world health organization, epilepsy is characterized by repetitive seizures and more electrical discharge in a group of brain neurons results ...
Shamzin Mamli, Hashem Kalbkhani
semanticscholar +3 more sources
Epilepsy is a brain disorder that many persons of different ages in the world suffer from it. According to the world health organization, epilepsy is characterized by repetitive seizures and more electrical discharge in a group of brain neurons results ...
Shamzin Mamli, Hashem Kalbkhani
semanticscholar +3 more sources
Automatic seizure detection based on Gray Level Co-occurrence Matrix of STFT imaged-EEG
Biomedical Signal Processing and Control, 2023Haniye Shayeste, B. M. Asl
semanticscholar +3 more sources
Computer Methods and Programs in Biomedicine, 2021
Hao Chen, Wei Li, Youyu Zhu
semanticscholar +3 more sources
Hao Chen, Wei Li, Youyu Zhu
semanticscholar +3 more sources
Gray level co-occurrence matrix and random forest based acute lymphoblastic leukemia detection
Biomedical Signal Processing and Control, 2017Sonal Mishra +3 more
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Detection of Common Types of Eczema Using Gray Level Co-occurrence Matrix and Support Vector Machine
International Conference on Computer and Automation Engineering, 2023Many people are being affected by eczema around the world. In the Philippines, the most common types of eczema are atopic dermatitis, contact dermatitis, and nummular dermatitis.
Sophia Gabrielle S. Jardeleza +3 more
semanticscholar +1 more source
Science of the Total Environment, 2022
Urban green space (UGS) is a complex and highly dynamic interface between people and nature. The existing methods of quantifying and evaluating UGS are mainly implemented on the surface features at a landscape scale, and most of them are insufficient to ...
Chenghan Xie +4 more
semanticscholar +1 more source
Urban green space (UGS) is a complex and highly dynamic interface between people and nature. The existing methods of quantifying and evaluating UGS are mainly implemented on the surface features at a landscape scale, and most of them are insufficient to ...
Chenghan Xie +4 more
semanticscholar +1 more source
Microscopy and Microanalysis, 2021
Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy.
Lazar Davidovic +7 more
semanticscholar +1 more source
Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy.
Lazar Davidovic +7 more
semanticscholar +1 more source

