IEEE Trans Image Process - A completed modeling of local binary pattern operator for texture classification.

Tópicos

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Resumo

In this correspondence, a completed modeling of the local binary pattern (LBP) operator is proposed and an associated completed LBP (CLBP) scheme is developed for texture classification. A local region is represented by its center pixel and a local difference sign-magnitude transform (LDSMT). The center pixels represent the image gray level and they are converted into a binary code, namely CLBP-Center (CLBP_C), by global thresholding. LDSMT decomposes the image local differences into two complementary components: the signs and the magnitudes, and two operators, namely CLBP-Sign (CLBP_S) and CLBP-Magnitude (CLBP_M), are proposed to code them. The traditional LBP is equivalent to the CLBP_S part of CLBP, and we show that CLBP_S preserves more information of the local structure than CLBP_M, which explains why the simple LBP operator can extract the texture features reasonably well. By combining CLBP_S, CLBP_M, and CLBP_C features into joint or hybrid distributions, significant improvement can be made for rotation invariant texture classification.

Resumo Limpo

correspond complet model local binari pattern lbp oper propos associ complet lbp clbp scheme develop textur classif local region repres center pixel local differ signmagnitud transform ldsmt center pixel repres imag gray level convert binari code name clbpcenter clbpc global threshold ldsmt decompos imag local differ two complementari compon sign magnitud two oper name clbpsign clbps clbpmagnitud clbpm propos code tradit lbp equival clbps part clbp show clbps preserv inform local structur clbpm explain simpl lbp oper can extract textur featur reason well combin clbps clbpm clbpc featur joint hybrid distribut signific improv can made rotat invari textur classif

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