Fingerprint Image Enhancement Using STFT Analysis

Contrary to popular belief, despite decades of research in fingerprints, reliable fingerprint recognition is an open problem. Extracting features out of poor quality prints is the most challening problem faced in this area. This paper introduces a new approach for fingerprint enhancement based on Short Time Fourier Transform(STFT) Analysis. STFT is a well known technique to analyze non-stationary signals. We extend its application to 2D images. The algorithm simultaneously estimates all the intrinsic properties of the fingerprints such as the foreground region mask, local ridge orientation and local frequency orientation. Furthermore we propose a probabilistic approach of robustly estimating these parameters. We compare the proposed approach to other filtering approaches and show that our technique performs favorably. We also objectively measure the improvement in recognition rate due to our enhancement. We obtain a 17% improvement in the recognition rate on a set of 800 images from the FVC2002 database. Sharat S. Chikkerur is a member of the Center for Unified Biometrics and Senors at the University at Buffalo (UB). He is currently a M.S student in the Department of Electrical Engineering. His research interests include image analysis, physical modeling in images,biometrics and pattern recognition. Alexander N. Cartwright is an Associate Professor of Electrical Engineering, a participating faculty in the Center for Unified Biometrics and Sensors, Director of the Institute for Lasers, Photonics and Biophotonics at the University at Buffalo (UB), and Co-Director of the Electronics Packaging Laboratory at the UB. He received the B.S. and Ph.D. degrees in electrical and computer engineering from The University of Iowa, Iowa City, in 1989 and 1995, respectively. Dr. Cartwright’s research is focused on III-N materials, quantum dot materials, image processing for optical nondestructive testing of stress and strain for device reliability, nanophotonics and nanoelectronics. Venugopal Govindaraju is a professor of Computer Science and Engineering at State University of New York at Buffalo, Founding director of CUBS, Center for Unified Biometrics and Sensors and Associate Director of CEDAR, the Center of Excellence for Document Analysis and Recognition at his university. He received his Ph.D degree in Computer Science at the University at Buffalo in 1992. His research is focused on Biometrics, Document Image Analysis and Pattern Recognition in general. He is a fellow of the IAPR and serves on the editing board of IEEE Transactions on Pattern Analysis and Machine Intelligence, the IEEE Transactions on Systems, Man, and Cybernetics (B), the International Journal for Document Analysis and Recognition, and The Journal of Pattern Recognition. Fingerprint Image Enhancement Using STFT Analysis