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Multi-Scale Shape Index-Based Local Binary Patterns for Texture Classification

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Tarih
2020
Yazar
Alpaslan, N. and Hanbay, K.
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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. © 1994-2012 IEEE.
Bağlantı
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085516949&doi=10.1109%2fLSP.2020.2987474&partnerID=40&md5=79b83a4445810a78e75d97b84a533289
http://acikerisim.bingol.edu.tr/handle/20.500.12898/3959
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