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Local binary pattern (LBP) and its variants have been successfully applied in texture feature extraction. However, it is hard for most LBP-based methods to effectively describe and distinguish the local neighborhoods with similar structures (that is, the calculated feature patterns are identical) but different contrasts or grayscales. To alleviate such problems, we propose a novel global refined local binary pattern (GRLBP) by analyzing the nature of pixel intensity distribution in local neighborhoods. GRLBP consists of two descriptors called magnitude refined local sign binary pattern (MRLBP_S) and center refined local magnitude binary pattern (CRLBP_M). MRLBP_S distinguishes local neighborhoods with contrast differences by using global magnitude anchors to refine local sign patterns. And CRLBP_M identifies local neighborhoods with grayscale differences by employing global central grayscale anchors to refine …