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Radiomic Characterization and Automated Classification of Drusen Substructure Phenotype Associated with High-Risk Dry Age-Related Macular Degeneration. [PDF]
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Использование алгоритма GLCM для проведения классификации изображений
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MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification
Computerized Medical Imaging and Graphics, 2023Distinguishing malignant from benign lesions has significant clinical impacts on both early detection and optimal management of those early detections. Convolutional neural network (CNN) has shown great potential in medical imaging applications due to its powerful feature learning capability.
Shu, Zhang +8 more
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Source camera identification using GLCM
2015 IEEE International Advance Computing Conference (IACC), 2015Digital images are becoming main focus of work for the researchers. Digital image forensics (DIF) is at the forefront of security techniques, aiming to restore the lost trust in digital imagery by uncovering digital counterfeiting techniques. Source camera identification provides different ways to identify the characteristics of the digital devices ...
Nilambari Kulkarni, Vanita Mane
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GLCM-based fingerprint recognition algorithm
2011 4th IEEE International Conference on Broadband Network and Multimedia Technology, 2011An efficient and reliable fingerprint recognition system is the fundamental need of contemporary living. Beside forensic use, it has been deployed in a large number of commercial applications recently. In this paper, a new method for fingerprint recognition is introduced. The Core point is found initially using Poincare Index method.
Amjad Ali, Xiaojun Jing, Nasir Saleem
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Pattern-based image retrieval using GLCM
Neural Computing and Applications, 2018Gray-level co-occurrence matrix (GLCM) is one of the oldest techniques used for texture analysis. It has two important parameters, i.e., distance and direction. In this paper, various combinations of distance and directional angles used for GLCM calculation are analyzed in order to recognize certain patterned images based on their textural features. In
Divya Srivastava +3 more
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GLCM parameters of channel texture analysis
SEG Technical Program Expanded Abstracts 2011, 2011Summary Channel texture is an acoustic expression of a fluvial facies derived from 3D seismic data. The Gray Level Cooccurrence Matrix (GLCM) technique has been proven to be a promising method for seismic texture analysis. However, while we try to extract seismic texture attributes, there is uncertainty on how to select the optimal GLCM parameters ...
Zhiguo Wang, Cheng Yin, Wei Zhao
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Texture Image Segmentation Based on GLCM
Applied Mechanics and Materials, 2012The paper proposed a method on marble texture image segmentation based on Gray Level Co-occurrence Matrix (GLCM). At first, compute the Contrast matrix on basis of GLCM. Then choose the maximum of the matrix as the threshold to segment the object. At last extract the object contour with curve fitting method.
Min Li, Jian Jun Liao
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DCT based texture watermarking using GLCM
2010 IEEE 2nd International Advance Computing Conference (IACC), 2010We present a novel DCT technique for digital watermarking of textured images based on the concept of gray-level co-occurrence matrix (GLCM). We provide analysis to describe the behavior of the method in terms of correlation as a function of the offset for textured images.
Sushila Kamble +3 more
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