LETRIST: Locally Encoded Transform Feature Histogram for Rotation-Invariant Texture Classification.
IEEE Transactions on Circuits and Systems for Video Technology(2018)
摘要
Classifying texture images, especially those with significant rotation, illumination, scale, and viewpoint changes, is a fundamental and challenging problem in computer vision. This paper proposes a simple yet effective image descriptor, called Locally Encoded TRansform feature hISTogram (LETRIST), for texture classification. LETRIST is a histogram representation that explicitly encodes the joint ...
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关键词
Transforms,Feature extraction,Histograms,Computational modeling,Lighting,Robustness,Quantization (signal)
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