Abstract
In recent years, binary keypoint descriptors have become ubiquitous in CV applications for their efficiency in computation. However, existing binary keypoint descriptors still face the problem of being less robust and discriminative. To tackle this problem, this paper presents a binary keypoint descriptor based on a newly proposed local pattern named local hierarchical octagon pattern (LHOP). The LHOP descriptor is much faster than SURF and ORB descriptors by creatively combing a newly designed orientation estimation method and the slanted integral image. Compared to the state-of-the-art keypoint descriptors, the main features of LHOP descriptor can be highlighted as follows: (1) It is robust. (2) It is efficient to compute. (3) It is highly discriminative. (4) It is memory saving and compact. Experimental results demonstrate that LHOP descriptor is at least 102 times faster than SIFT descriptor under almost the same matching performance. Moreover, the LHOP descriptor offers the better matching performance compared to other binary descriptors.
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Acknowledgements
Thanks to all the persons who have actively contributed to the progress of this paper with their advice and efforts. In addition, thanks to the associate editors and the reviewers for the time and effort spent handling this paper. This work was supported by the Science and Technology Innovation seedling project of Sichuan (2016–2017).
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Jin, L., Liu, Y., Xu, Z., Zheng, Y., Du, S. (2019). Robust Binary Keypoint Descriptor Based on Local Hierarchical Octagon Pattern. In: Jiang, M., Ida, N., Louis, A., Quinto, E. (eds) The Proceedings of the International Conference on Sensing and Imaging. ICSI 2017. Lecture Notes in Electrical Engineering, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-91659-0_21
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DOI: https://doi.org/10.1007/978-3-319-91659-0_21
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