Login
Talks & Seminars
Title: Level-3 Friction Ridge Pattern Analysis
Mayank Vatsa, West Virginia University
Date & Time: September 6, 2008 10:30
Venue: Conference Room, 01st floor, 'C' Block, Kanwal Rekhi Building
Abstract:

Fingerprint features have been widely used for verifying the identity of an individual. Automatic fingerprint verification systems use ridge flow patterns and general morphological information for broad classification, and minutiae information for verification. The ridge flow patterns and morphological information are referred to as level-1 features, while ridge endings and bifurcations, also known as minutiae, are referred to as level-2 features. With the availability of high resolution fingerprint sensors, it is now feasible to capture more intricate features such as ridge path deviation, ridge edge features, ridge width and shape, local ridge quality, distance between pores, size and shape of pores, position of pores on the ridge, permanent scars, incipient ridges, and permanent flexure creases. These fine details are characterized as level-3 features and play an important role in matching and improving the verification accuracy.

The main objective of my PhD research is to develop a fast and accurate automated fingerprint verification algorithm that incorporates both level-2 and level-3 features. First, a fast Mumford-Shah curve evolution algorithm is used to extract four level-3 features namely, pores, ridge contours, dots, and incipient ridges. For improving the fingerprint verification performance, we further propose an evidence-theoretic multimodal unification approach using belief functions that takes into account the variability in level-2 and level-3 characteristics. Experimental results and statistical tests on a database of 700 classes show the effectiveness of the proposed algorithms. Compared to existing algorithms, the proposed approach is computationally efficient, and the verification accuracy is not compromised even with partial fingerprints.

Speaker Profile:
Mayank Vatsa received the M.S. degree in computer science in 2005 and is currently working toward the Ph.D. degree in computer science at West Virginia University, Morgantown, USA. He was actively involved in the development of a multimodal biometric system, which includes face, fingerprint, signature, and iris recognition at Indian Institute of Technology, Kanpur, India, from July 2002 to July 2004. He has 73 publications in refereed journals, book chapters, and conferences. His current areas of interest include information fusion, biometrics, digital forensics, computer vision, image processing, and belief theory. Mayank is a member of the IEEE, Computer Society and ACM. He is also a member of the Phi Kappa Phi, Tau Beta Pi, Sigma Xi, Upsilon Pi Epsilon, and Eta Kappa Nu honor societies. He was the recipient of four best paper awards.
List of Talks

Webmail

Username:
Password:
Faculty CSE IT
Forgot Password
    [+] Sitemap     Feedback