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.
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Sulc, M., Matas, J. (2015). Fast Features Invariant to Rotation and Scale of Texture. In: Agapito, L., Bronstein, M., Rother, C. (eds) Computer Vision - ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science(), vol 8926. Springer, Cham. https://doi.org/10.1007/978-3-319-16181-5_4
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