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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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Computer-aided Diagnosis of the Solitary Pulmonary Nodule1

TL;DR: Computer-aided diagnosis has the potential to assist radiologists in the task of differentiating solitary pulmonary nodules and in the management of these patients.
Journal ArticleDOI

Texture feature benchmarking and evaluation for historical document image analysis

TL;DR: A benchmarking of the most classical and widely used texture-based feature sets has been conducted using a classical texture- based pixel-labeling scheme on a large corpus of historical documents to provide a useful benchmark in terms of performance and computational cost for current and future research efforts in HDIA.
Journal ArticleDOI

A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography

TL;DR: This work provides a set of optimal texture features which are suitable for distinguishing between hyperacute ischemic lesions and their corresponding contralateral brain tissue in noncontrast CT.
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Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology.

TL;DR: The results indicate that the selected multispectral bands have more discriminant information than a single spectral band or all spectral bands for mitotic figures, validating the interest of using mult ispectral images to improve the quality of the diagnostic in histopathology.
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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