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Texture Classification

Texture Classification is a fundamental issue in computer vision and image processing, playing a significant role in many applications such as medical image analysis, remote sensing, object recognition, document analysis, environment modeling, content-based image retrieval and many more.

Source: Improving Texture Categorization with Biologically Inspired Filtering

Papers

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Showing 151–160 of 206 papers

TitleStatusHype
Texture analysis using deterministic partially self-avoiding walk with thresholds—0
Fast deterministic tourist walk for texture analysis—0
Evaluating Urbanization from Satellite and Aerial Images by means of a statistical approach to the texture analysis—0
Document Image Coding and Clustering for Script Discrimination—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
Equiangular Kernel Dictionary Learning With Applications to Dynamic Texture Analysis—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
Learning rotation invariant convolutional filters for texture classificationCode0
Fractal Dimension Invariant Filtering and Its CNN-based Implementation—0
A non-extensive entropy feature and its application to texture classification—0
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