Computer Science ›› 2017, Vol. 44 ›› Issue (12): 292-297, 309.doi: 10.11896/j.issn.1002-137X.2017.12.053

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Sample Point Group Based Binary Method for Robust Binary Descriptor

LIU Hong-min, LI Lu and WANG Zhi-heng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Since a binary descriptor with a sampling pattern usually extracts information with high correlation and behaves less robust,through improving the retina sampling pattern,this paper proposed a novel sampling point group based binaryzation strategy to generate descriptor.Firstly,by reducing the number of sampling layers and enlarging the distance between sample points,an improved retina sampling pattern with low sampling density and low overlapping between sampling fields is designed.Then a sample point group is constructed by extracting some points surrounding a sample point in the pattern.Next,the binary result of a pair of sample point group is determined by voting their corresponding points’ intensity tests.Finally,the image gradient information is also computed and added to the final descriptor so as to enhance descriptor’s description power.Experiment results reveal that the proposed descriptor is robust to various image transformations and outperforms the four compared descriptors.

Key words: Feature matching,Sampling pattern,Binary descriptor,Sample point team

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