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Fast Features Invariant to Rotation and Scale of Texture

  • Milan SulcEmail author
  • Jiri Matas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8926)

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.

Keywords

Texture Classification LBP LBP-HF Histogram SVM Feature maps Ffirst 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Center for Machine Perception, Department of Cybernetics, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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