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Depth analysis of monocular natural scenes using gray level co-occurrence matrix
2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012), 2012Representation of depth in a real world environment is an essential attribute of its semantic representation. A coarse estimate of image-depth (defined as mean distance between the object and the observer) is relevant for identifying the context of the scene and can be used to facilitate search and recognition of objects.
N. P. Rath +2 more
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2020
This chapter explores diagnosis of the breast tissues as normal, benign, or malignant in digital mammography, using computer-aided diagnosis (CAD). System for the early diagnosis of breast cancer can be used to assist radiologists in mammographic mass detection and classification.
Khaddouj Taifi +4 more
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This chapter explores diagnosis of the breast tissues as normal, benign, or malignant in digital mammography, using computer-aided diagnosis (CAD). System for the early diagnosis of breast cancer can be used to assist radiologists in mammographic mass detection and classification.
Khaddouj Taifi +4 more
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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), 2023Chen Meilong +3 more
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JPEG image tampering localization based on normalized gray level co-occurrence matrix
Multimedia Tools and Applications, 2018To locate the tampered region of double compressed JPEG images, one of the most effective methods is based on the statistical characteristic of the images. After tampering operation, the tampered region and the original region will have different statistical distributions. And according to this cue, the histogram of DCT coefficients can be moded as the
Fei Xue, Wei Lu, Ziyi Ye, Hongmei Liu
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Identifikasi Citra Massa Kistik Berdasar Fitur Gray-Level Co-Occurrence Matrix
Seminar Nasional Aplikasi Teknologi Informasi (SNATI), 2009We have studied the effectiveness of using texture features derived from gray-level co-occurrence matrix(GLCM) matrices for classification of cystic mass and non-cystic mass in ultra sonograms. Twenty-three (23)region of interest (ROIs) containing cystic masses and fifty-five (55) non-cystic masses were extracted from ultrasonogram for this study.
Wibawanto, Hari +3 more
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Speckle Quality Evaluation Based on Gray Level Co-Occurrence Matrix
Laser & Optoelectronics Progress, 2021初录 Chu Lu +4 more
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Automatic seizure detection based on Gray Level Co-occurrence Matrix of STFT imaged-EEG
Biomedical Signal Processing and Control, 2023Babak
exaly
Fingerprint Recognition Algorithm Using Gray level Co-Occurrence Matrix
The Journal of Korean Institute of Information Technology, 2014openaire +1 more source
Analysis of texture feature extracted by gray level co-occurrence matrix
Journal of Computer Applications, 2009Li-hong YUAN +3 more
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