Finger-Knuckle-Print Recognition: A Preliminary Review
LU Jingting1,2, JIA Wei2, YE Hui1, ZHAO Yang2, MIN Hai2, YU Ye2, HU Rongxiang3
1.Institute of Industry and Equipment Technology, Hefei University of Technology, Hefei 230009 2.School of Computer and Information, Hefei University of Technology, Hefei 23009 3.Institute of Nuclear Energy Safety Technology, Hefei Institutes of Physical Science, Chinese Academy of Sceinces, Hefei 230031
Abstract：Compared with face, fingerprint, and iris based biometrics systems, finger-knuckle-print recognition based biometrics system has stable features, and it can be collected by low cost device and be easily combined with palmprint, finger vein, and hand shape recognition to form a robust system. In this paper, the definition, the data acquisition and the preprocessing of finger-knuckle-print recognition are firstly introduced. Then, the feature extraction and matching algorithms as well as multi-modal methods are reviewed. The effective finger-knuckle-print recognition algorithms are roughly divided into six categories: texture-based algorithm, structure-based algorithm, subspace learning-based algorithm, correlation filter-based algorithm, local descriptor-based algorithm and orientation coding-based algorithm. Finally, the development tendency of finger-knuckle-print recognition is forecasted.
陆劲挺,贾伟,叶慧,赵洋,闵海,余烨,胡戎翔. 指节纹识别综述*[J]. 模式识别与人工智能, 2017, 30(7): 622-636.
LU Jingting, JIA Wei, YE Hui, ZHAO Yang, MIN Hai, YU Ye, HU Rongxiang. Finger-Knuckle-Print Recognition: A Preliminary Review. , 2017, 30(7): 622-636.
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