标题:Finger vein image retrieval via affinity-preserving K-means hashing
作者:Su, Kun ;Yang, Gongping ;Yang, Lu ;Yin, Yilong
通讯作者:Yang, Gongping
作者机构:[Su, Kun ;Yang, Gongping ;Yin, Yilong ] School of Computer Science and Technology, Shandong University, Jinan, China;[Yang, Lu ;Yin, Yilong ] School o 更多
会议名称:2017 IEEE International Joint Conference on Biometrics, IJCB 2017
会议日期:1 October 2017 through 4 October 2017
来源:IEEE International Joint Conference on Biometrics, IJCB 2017
出版年:2018
卷:2018-January
页码:375-382
DOI:10.1109/BTAS.2017.8272720
摘要:Efficient identification of finger veins is still a challenging problem due to the increasing size of the finger vein database. Most leading finger vein image identification methods have high-dimensional real-valued features, which result in extremely high computation complexity. Hashing algorithms are extraordinary effective ways to facilitate finger vein image retrieval. Therefore, in this paper, we proposed a finger vein image retrieval scheme based on Affinity-Preserving K-means Hashing (APKMH) algorithm and bag of subspaces based image feature. At first, we represent finger vein image by Nonlinearly Sub-space Coding (NSC) method which can obtain the discriminative finger vein image features. Then the features space is partitioned into multiple subsegments. In each subsegment, we employ the APKMH algorithm, which can simultaneously construct the visual codebook by directly k-means clustering and encode the feature vector as the binary index of the codeword. Experimental results on a large fused finger vein dataset demonstrate that our hashing method outperforms the state-of-the-art finger vein retrieval methods. © 2017 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046281603&doi=10.1109%2fBTAS.2017.8272720&partnerID=40&md5=2584f11896ef516e4c125b43b2b0b9ab
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