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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 91–100 of 206 papers

TitleStatusHype
Grey Level Co-occurrence Matrix (GLCM) Based Second Order Statistics for Image Texture Analysis—0
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning—0
Heterogeneous patterns enhancing static and dynamic texture classification—0
Fast and accurate computation of orthogonal moments for texture analysis—0
Characterization of migrated seismic volumes using texture attributes: a comparative study—0
Human activity recognition from mobile inertial sensors using recurrence plots—0
Identifying the Origin of Finger Vein Samples Using Texture Descriptors—0
Rotation Differential Invariants of Images Generated by Two Fundamental Differential Operators—0
A PCA-Based Convolutional Network—0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset—0
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