Methodology for partial fingerprint enrollment and authentication on mobile devices

The reduced platen area of fingerprint sensors in mobile devices results in acquisition of partial fingerprints. Existing fingerprint enrollment schemes for small area sensors are tedious and have an uncertainty of complete finger coverage during scanning. We propose a novel enrollment protocol for small area rectangular sensors that maximizes finger coverage within few scans. Also, due to presence of insufficient minutiae, accuracy of minutiae-based fingerprint matching algorithms degrades significantly when applied for partial-to-partial fingerprint matching. Instead, we propose a matching algorithm that utilizes multi-scale texture descriptors, namely, Accelerated KAZE (A-KAZE). Experiments on FVC 2000, 2002 and in-house databases indicate that A-KAZE gives promising accuracy. On a Samsung Galaxy Note II N7100 (Quad-core 1.6 GHz, 2GB RAM), average time taken for template generation and 1×1 matching of fingerprint of size 237×117 pixels is 86 ms and 19 ms respectively.

[1]  Tsuyoshi Isshiki,et al.  SIFT-based algorithm for fingerprint authentication on smartphone , 2015, 2015 6th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES).

[2]  Anil K. Jain,et al.  FVC2000: Fingerprint Verification Competition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[4]  Anil K. Jain,et al.  FVC2002: Second Fingerprint Verification Competition , 2002, Object recognition supported by user interaction for service robots.

[5]  Adrien Bartoli,et al.  KAZE Features , 2012, ECCV.

[6]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Bala Srinivasan,et al.  Partial Fingerprint Matching through Region-Based Similarity , 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

[8]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[9]  Xin Yang,et al.  LDB: An ultra-fast feature for scalable Augmented Reality on mobile devices , 2012, 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[10]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[11]  Yi Chen,et al.  Dots and Incipients: Extended Features for Partial Fingerprint Matching , 2007, 2007 Biometrics Symposium.

[12]  Adrien Bartoli,et al.  Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces , 2013, BMVC.

[13]  Venu Govindaraju,et al.  A minutia-based partial fingerprint recognition system , 2005, Pattern Recognit..

[14]  Hee-seung Choi,et al.  Fingerprint Mosaicking by Rolling and Sliding , 2005, AVBPA.

[15]  Sargur N. Srihari,et al.  Use of ridge points in partial fingerprint matching , 2007, SPIE Defense + Commercial Sensing.