期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/705710
出版社：Hindawi Publishing Corporation
摘要：This paper explores an inner-knuckle-print (IKP) biometric recognition, based on mobile phone. Since IKP characteristics are captured by using mobile phone camera, the greatest challenge is that IKP images from the same hand have different illumination, posture, and background. In order to construct autonomous and robust recognition, we present a range of techniques as follows. Firstly, the hand region is preprocessed by using mean shift (MS) and -means clustering. Secondly, the region of interest (ROI) of IKP is segmented and normalized. Thirdly, the IKP feature is extracted by using 2D Gabor filter with proper orientation and frequency. Finally, histogram of orientation gradient (HOG) algorithm is applied for matching. According to the experimental results, the proposed method is capable of achieving considerable recognition accuracy.
