ROTATION-INVARIANT LOCAL RADIUS INDEX: A COMPACT TEXTURE SIMILARITY FEATURE FOR CLASSIFICATION

This paper proposes a new rotation-invariant texture similarity feature, called Rotation-Invariant Local Radius Index (RILRI). Whereas the original LRI was designed for applications that are sensitive to rotation and aimed to penalize rotation monotonically, the new rotation-invariant LRI is well suited to texture classification. When combined with frequency domain contrast information and the well known Local Binary Patterns (LBP) feature, the proposed metric has comparable texture classification accuracy to state-of-the-art metrics, when tested on the Outex and CUReT databases. Moreover, it has an approximately ten times lower dimensional feature vector and requires substantially less computation than other state-of-the-art texture features, such as those based on LBP.