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Efficient and distinctive binary descriptor for rotated circular image recognition

  • Dongbo ZhangEmail author
  • Honglei Chen
  • Feng Yin
  • Zhiqiang Chen
  • Hongzhong Tang
  • Haixia Xu
Original Paper
  • 47 Downloads

Abstract

Based on pairs of spatial symmetric patches, a novel efficient and distinctive binary descriptor is proposed in this paper for rotated circular image recognition. To achieve rotation invariance during feature computation, a local coordinate system is first found with radial transform technology. On the basis of that, local binary patterns against rotation can be extracted. Meanwhile, the circular image is divided into a set of overlapped annular regions, and pairs of patch description are constructed with histogram within the ring. Finally, the rotation-invariant image description can be obtained by concatenating the ring features from inner to outer. The performance of proposed method is tested with three datasets, i.e., the euro coins, QQ expression and car logo. The test results show that its recognition accuracies reach 100, 100 and 97.07%, respectively, which are superior to the results of traditional methods based on LBP feature. And our method presents competitive performance contrasted to recently proposed LBP invariants, i.e., R_LBP, CS_LBP and PRI_COLBP, and conventional floating and binary descriptors, such as SIFT, SURF, BRISK and FREAK. Moreover, the algorithm is efficient, as single-point feature computation needed only 0.045 ms.

Keywords

Image descriptor Local binary patterns Image recognition Rotation invariance 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China [Grant Number 61602397], the Natural Science Foundation of Hunan Province [Grant Numbers 2017JJ2251, 2017JJ3315] and the Key Discipline Construction Project of Hunan Province.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.The College of Information EngineeringXiangtan UniversityXiangtanChina
  2. 2.Key Laboratory of Intelligent Computing and Information Processing of Ministry of EducationXiangtanChina

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