Abstract

In this work, we introduce a novel pairwise rotation invariant co-occurrence local binary pattern (PRI-CoLBP) feature which incorpo- rates two types of context - spatial co-occurrence and orientation co- occurrence. Different from traditional rotation invariant local features, pairwise rotation invariant co-occurrence features preserve relative angle between the orientations of individual features. The relative angle de- picts the local curvature information, which is discriminative and rota- tion invariant. Experimental results on the CUReT, Brodatz, KTH-TIPS texture dataset, Flickr Material dataset, and Oxford 102 Flower dataset further demonstrate the superior performance of the proposed feature on texture classification, material recognition and flower recognition tasks.