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A Novel IKP-Based Biometric Recognition Using Mobile Phone Camera

Author

Listed:
  • Xue-Miao Xu
  • Xiao-Zheng Lai
  • Qiang Jin
  • Xue-Han Yuan
  • Sheng-Li Lai
  • Yan-Wen Lin
  • Jian-Wen Huang

Abstract

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 K -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.

Suggested Citation

  • Xue-Miao Xu & Xiao-Zheng Lai & Qiang Jin & Xue-Han Yuan & Sheng-Li Lai & Yan-Wen Lin & Jian-Wen Huang, 2015. "A Novel IKP-Based Biometric Recognition Using Mobile Phone Camera," International Journal of Distributed Sensor Networks, , vol. 11(10), pages 705710-7057, October.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:10:p:705710
    DOI: 10.1155/2015/705710
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