Mobile Networks and Management. 9th International Conference, MONAMI 2017, Melbourne, Australia, December 13-15, 2017, Proceedings

Research Article

A Robust Contactless Fingerprint Enhancement Algorithm

Download68 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-90775-8_11,
        author={Xuefei Yin and Yanming Zhu and Jiankun Hu},
        title={A Robust Contactless Fingerprint Enhancement Algorithm},
        proceedings={Mobile Networks and Management. 9th International Conference, MONAMI 2017, Melbourne, Australia, December 13-15, 2017, Proceedings},
        proceedings_a={MONAMI},
        year={2018},
        month={5},
        keywords={Contactless fingerprint enhancement Sinusoidal-shaped filter Ridge orientation Ridge frequency Fingerprint},
        doi={10.1007/978-3-319-90775-8_11}
    }
    
  • Xuefei Yin
    Yanming Zhu
    Jiankun Hu
    Year: 2018
    A Robust Contactless Fingerprint Enhancement Algorithm
    MONAMI
    Springer
    DOI: 10.1007/978-3-319-90775-8_11
Xuefei Yin1,*, Yanming Zhu1,*, Jiankun Hu1,*
  • 1: University of New South Wales
*Contact email: xuefei.yin@student.unsw.edu.au, yanming.zhu@student.unsw.edu.au, J.Hu@adfa.edu.au

Abstract

Compared to contact fingerprint images, contactless fingerprint images have three particular characteristics: (1) contactless fingerprint images have less noise than contact fingerprint images; (2) there are less discontinuities of ridges in contactless fingerprint images; and (3) the ridge-valley pattern of contactless fingerprint is much more unclear than that of contact fingerprint images. These properties increase a great difficulty to the contactless fingerprint enhancement. In this paper, we propose a robust contactless fingerprint enhancement algorithm based on simple sinusoidal-shaped filter kernel to fully take advantage of the properties of contactless fingerprint. First, an effective preprocessing is proposed to preliminarily strengthen the ridge-valley contrast of contactless fingerprint images. Then, simple sinusoidal-shaped filter kernel is proposed to enhance the contactless fingerprint images. Finally, we propose a score-filtering procedure to effectively recover the ridge-valley pattern. Comprehensive experiments were performed to evaluate the proposed method from aspects of image quality, minutiae extraction and fingerprint verification. Experimental results demonstrate the high performance of the proposed algorithm in contactless fingerprint enhancement.