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Sādhanā

, 44:161 | Cite as

Towards smartphone-based touchless fingerprint recognition

  • Parmeshwar BirajadarEmail author
  • Meet Haria
  • Pranav Kulkarni
  • Shubham Gupta
  • Prasad Joshi
  • Brijesh Singh
  • Vikram Gadre
Article

Abstract

The widely used conventional touch-based fingerprint identification system has drawbacks like the elastic deformation due to nonuniform pressure, fingerprints collection time and hygiene. To overcome these drawbacks, recently the touchless fingerprint technology is gaining popularity and various touchless fingerprint acquisition solutions have been proposed. Nowadays due to the wide use of the smartphone in various biometric applications, smartphone-based touchless fingerprint systems using an embedded camera have been proposed in the literature. These touchless fingerprint images are very different from conventional ink-based and live-scan fingerprints. Due to varying contrast, illumination and magnification, the existing touch-based fingerprint matchers do not perform well while extracting reliable minutiae features. A touchless fingerprint recognition system using a smartphone is proposed in this paper, which incorporates a novel monogenic-wavelet-based algorithm for enhancement of touchless fingerprints using phase congruency features. For the comparative performance analysis of our system, we created a new touchless fingerprint database using the developed android app and this is publicly made available along with its corresponding live-scan images for further research. The experimental results in both verification and identification mode on this database are obtained using three widely used touch-based fingerprint matchers. The results show a significant improvement in Rank-1 accuracy and equal error rate (EER) achieved using the proposed system and the results are comparable to that of the touch-based system.

Keywords

Biometrics touchless fingerprint recognition monogenic wavelet phase congruency fingerprint enhancement android app 

Notes

Acknowledgements

This work was supported by the NCETIS (National Center of Excellence in Technology for Internal Security) and MHRD-TEQIP-KITE, a TEQIP initiative of the Ministry of Human Resource Development at IIT Bombay. The authors would also like to thank the students of IIT Bombay, for helping them create the touchless fingerprint database. They also wish to acknowledge the active participation and support of Shri Balsing Rajput and Shri Deepak Dhole of Department of Cyber Maharashtra, Mumbai.

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Copyright information

© Indian Academy of Sciences 2019

Authors and Affiliations

  1. 1.Indian Institute of Technology BombayMumbaiIndia
  2. 2.Department of Cyber MaharashtraMumbaiIndia

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