Open AccessA Novel Fast and Robust Binary Affine Invariant Descriptor for Image Matching
Author(s) -
Xiujie Qu,
Fei Zhao,
Mengzhe Zhou,
Haili Huo
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/129230
Subject(s) - affine transformation , local binary patterns , mathematics , invariant (physics) , affine combination , affine shape adaptation , pattern recognition (psychology) , binary number , zoom , matching (statistics) , scale invariance , artificial intelligence , affine hull , transformation (genetics) , image matching , algorithm , computer vision , computer science , image (mathematics) , histogram , pure mathematics , affine space , statistics , biochemistry , chemistry , arithmetic , petroleum engineering , engineering , gene , mathematical physics , lens (geology)
As the current binary descriptors have disadvantages of high computational complexity, no affine invariance, and the high false matching rate with viewpoint changes, a new binary affine invariant descriptor, called BAND, is proposed. Different from other descriptors, BAND has an irregular pattern, which is based on local affine invariant region surrounding a feature point, and it has five orientations, which are obtained by LBP effectively. Ultimately, a 256 bits binary string is computed by simple random sampling pattern. Experimental results demonstrate that BAND has a good matching result in the conditions of rotating, image zooming, noising, lighting, and small-scale perspective transformation. It has better matching performance compared with current mainstream descriptors, while it costs less time
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