IEEE Seminar Announcement

Abstract: Among all biometric indicators, fingerprints have one of the highest levels of reliability and have been extensively studied both in the context of forensic science and image processing. Fingerprint identification is the process by which a fingerprint impression is associated with the identity of an individual via a matching process. The problem of fingerprint matching involves determining the similarity between two fingerprint impressions by computing a matching score. A number of techniques have been proposed in the literature to represent and match fingerprint images. In this talk we will examine a few of these techniques. We will discuss the various challenges that an automated fingerprint system has to contend with both during image acquisition and image matching. Some of the research issues related to fingerprint identification, and the opportunities presented in this regard will also be outlined.

Speaker Bio: Arun Ross is an Assistant Professor with the Lane Department of Computer Science and Electrical Engineering at West Virginia University. His research interests include statistical pattern recognition, machine learning, data mining, and biometric authentication.

Ross received his B.E. (Hons.) degree in Computer Science from the Birla Institute of Technology and Science, Pilani (India), in 1996. He obtained his M.S. and Ph.D. degrees in Computer Science and Engineering from Michigan State University in 1999 and 2003, respectively. His Ph.D. Dissertation was titled, "Information Fusion in Fingerprint Authentication".

Between July 1996 and December 1997, Ross worked with the Design and Development group of Tata Elxsi (India) Ltd., in Bangalore. He also spent three summers (2000, 2001, and 2002) with the Imaging and Visualization group at Siemens Corporate Research, Inc., Princeton, working on fingerprint recognition algorithms.