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Multi-Scale Shape Index-Based Local Binary Patterns for Texture Classification
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DOI：10.1109/LSP.2020.2987474.png)
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摘要
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To enhance the weakness of Local Binary Pattern (LBP) and its state-of-the-art variants, this letter presents a new variant of the local concave microstructure pattern (LCvMSP). The proposed multi-scale shape index based texture descriptor is named as SI-LCvMSP. Contrarily to the original LBP and LCvMSP, SI-LCvMSP uses the shape index instead of the original texture image in the kernel function. The shape index is a differential calculation and it can be calculated from local second-order derivatives of texture images. It captures microstructure and macrostructure texture information mathematically. As textural features, we use multi-scale and multi-resolution shape index information as well as rotation-invariant uniform LBP. Thus, we obtain the discriminative feature representation schema to construct cross-scale joint coding. The proposed method has a high discriminability and is less sensitive to image transforms such as rotation and illumination. Experimental results show that the SI-LCvMSP descriptor can improve classification accuracy.
Keyword:
Shape
Indexes
Feature extraction
Kernel
Lighting
Windows
Histograms
Feature representation
local binary pattern
shape index
texture descriptors
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9.6
论文数:
1.1W
被引数:
1.7W
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