Journal ArticleDOI
Texture analysis using gray level run lengths
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TLDR
In this paper, a set of texture features based on gray level run lengths is described, and good classification results are obtained with these features on a sets of samples representing nine terrain types.About:
This article is published in Computer Graphics and Image Processing.The article was published on 1975-06-01. It has received 1848 citations till now. The article focuses on the topics: Image texture & Texture (geology).read more
Citations
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Journal ArticleDOI
Texture analysis of human liver.
TL;DR: To classify healthy and diseased livers by texture analysis (TA), the objective was to establish a categorical hierarchy of livers based on the properties of their texture.
Journal ArticleDOI
Automated diagnosis of epilepsy using CWT, HOS and texture parameters.
U. Rajendra Acharya,U. Rajendra Acharya,Ratna Yanti,Jia Wei Zheng,M. Muthu Rama Krishnan,Jen Hong Tan,Roshan Joy Martis,Choo Min Lim +7 more
TL;DR: This work proposes a method for the automated classification of EEG signals into normal, interictal and ictal classes using Continuous Wavelet Transform, Higher Order Spectra and textures, and observed that the SVM classifier with Radial Basis Function (RBF) kernel function yielded the best results.
Journal ArticleDOI
Challenges and Promises of PET Radiomics
TL;DR: In this paper, the authors describe the extraction of multiple, otherwise invisible, features from medical images that, with bioinformatic approaches, can be used to provide additional information that can predict underlying tumor biology and behavior.
Journal ArticleDOI
Toward a structural textural analyzer based on statistical methods
TL;DR: To mathematically verify that the features used with the SGLDM can be used to characterize the unit pattern and placement rules of a periodic texture, a mathematical tiling theory model is proposed and allows one to develop the mathematical machinery necessary to prove the result.
Journal ArticleDOI
Texture analysis of multiple sclerosis : a comparative study
TL;DR: It is suggested that texture analysis with the combined set of texture features may be equally good or more advantageous than the commonly used GLCM-based features alone in discriminating MS lesions and NWM/NAWM and in supporting early diagnosis of MS.
References
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Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Journal ArticleDOI
Gray-Level Manipulation Experiments for Texture Analysis
TL;DR: Some gray-level manipulation techniques are described, the first of which involves changing thegray-level distribution within the picture, and a method for extracting relatively noise-free objects from a noisy background is described.
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