A Conceptual Study on Image Enhancement Techniques for Fingerprint Images

Author:

K. Krishna Prasad1,Aithal P. S.2

Affiliation:

1. Research Scholar, College of Computer and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India

2. Principal Srinivas Institute of Management Studies, Pandeshwar, Mangalore – 575001, India

Abstract

Biometrics is an emerging field of research in recent years and has been devoted to the identification of individuals using one or more intrinsic physical or behavioral traits. Fingerprints are the prominent and widely acceptable biometric features compared to face, speech, iris, and other types of biometrics. Fingerprint characteristic or features are unique for everyone and which cannot change throughout the lifetime. Fingerprint biometrics is having applications in diverse fields like attendance system, criminology, mobile applications and logical access control system. This is the purpose behind the popularity of fingerprints as the biometric identifier. The biometric image captured through mobile supportive devices like the mobile camera or USB Fingerprint contains low-quality images. In fingerprint recognition system the quality of the image plays a very important role while matching two fingerprints. Most of the fingerprint recognition systems result in poor matching due to impurity or noisy images. So there is high necessity and scope for image preprocessing and enhancement techniques in order to improve the quality of fingerprint image and to obtain high accuracy in the matching process. In this paper, we discuss some approaches and methods for reducing noise or impurities and to improve the quality of the image before matching them. These techniques help the fingerprint recognition system to become robust and to obtain high quality in the matching process.

Publisher

Srinivas University

Subject

General Medicine

Reference18 articles.

1. Prabhakar, S., Pankanti, S., & Jain, A. K. (2003). Biometric recognition: Security and privacy concerns. IEEE security & privacy, 99(2), 33-42.

2. Lee, H. C., Ramotowski, R., &Gaensslen, R. E. (Eds.). (2001). Advances in fingerprint technology. CRC press.

3. Newham, E. (1995). The biometric report. SJB services, 733. [4] Moenssens, A. A. (1975). Fingerprint techniques. Chilton.

4. Lee, C., Lee, S., Kim, J., & Kim, S. J. (2006, January). Preprocessing of a fingerprint image captured with a mobile camera. In International Conference on Biometrics, Springer, Berlin, Heidelberg.348-355.

5. https://images.google.com/. (2017). Google.[online] Available at: https://images.google.com/ridge ending and bifurcation images [Accessed 18 Jul. 2017].

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