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Journal ArticleDOI

Texture analysis using gray level run lengths

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.
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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).

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Citations
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Proceedings ArticleDOI

A comparison of feature selection methods for machine learning based automatic malarial cell recognition in wholeslide images

TL;DR: The binary SVM classifier yields a superlative accuracy of 95.5% if the feature-selection is based on Kullback-Leibler distance between the two classes.
Proceedings ArticleDOI

Recognizing signs of malignancy — The quest for computer assisted cancer screening and diagnosis systems

TL;DR: Some of the major issues involved are discussed, some of the proposed solutions are examined and some comments about the state of the art are given.
Proceedings ArticleDOI

A comparative study of texture coarseness measures

TL;DR: This paper proposes to study the robustness and the relationship with human coARSeness perception of 17 classical measures of coarseness, in order to obtain a ranking of measures to identify those measures that have the highest relationship degree with perception and the least variation with the other image features.
Journal ArticleDOI

A novel method of determining breast cancer risk using parenchymal textural analysis of mammography images on an Asian cohort.

TL;DR: A novel method to predict breast cancer risk that combines new texture and mammographic density based image features is presented, which can be implemented to routine breast cancer screening strategies.
Proceedings ArticleDOI

Novel method for image splicing detection

TL;DR: An image splicing detection method based on texture features of spliced image is proposed that is very effective in detection of splicing forgery as marked by the results.
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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