Fast Features Invariant to Rotation and Scale of Texture

Abstract

A family of novel texture representations called Ffirst, the Fast Features Invariant to Rotation and Scale of Texture, is introduced. New rotation invariants are proposed, extending the LBP-HF features, improving the recognition accuracy. Using the full set of LBP features, as opposed to uniform only, leads to further improvement. Linear Support Vector Machines with an approximate $\chi ^2$ -kernel map are used for fast and precise classification. Experimental results show that Ffirst exceeds the best reported results in texture classification on three difficult texture datasets KTH-TIPS2a, KTH-TIPS2b and ALOT, achieving 88 %, 76 % and 96 % accuracy respectively. The recognition rates are above 99 % on standard texture datasets KTH-TIPS, Brodatz32, UIUCTex, UMD, CUReT.