Arun RossArun Ross

Arun Ross is a Robert C. Byrd Associate Professor in the Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, and the Assistant Director of the NSF Center for Identification Technology Research (CITeR). He received the B.E. (Hons.) degree in Computer Science from the Birla Institute of Technology and Science, Pilani, India, in 1996, and the M.S. and Ph.D. degrees in Computer Science and Engineering from Michigan State University, East Lansing, in 1999 and 2003,respectively. Between 1996 and 1997, he was with the Design and Development Group of Tata Elxsi (India) Ltd., Bangalore, India. He also spent three summers (2000 - 2002) with the Imaging and Visualization Group of Siemens Corporate Research, Inc., Princeton, NJ, working on fingerprint recognition algorithms. His research interests include pattern recognition, classifier fusion, machine learning, computer vision, and biometrics. He is actively involved in the development of biometrics and pattern recognition curricula at West Virginia University. He received the West Virginia University Foundation Award for Outstanding Teaching in 2011. He is the coauthor of Handbook of Multibiometrics and co-editor of Handbook of Biometrics. Arun is a recipient of NSF's CAREER Award and was designated a Kavli Frontier Fellow by the National Academy of Sciences in 2006. He is an Associate Editor of the IEEE Transactions on Image Processing and the IEEE Transactions on Information Forensics and Security.


Biometrics: Past, Present and Future


Biometrics is the science of establishing human identity based on the physical and behavioral attributes of an individual such as fingerprints, face, iris, voice and signature. In its simplest form, biometric recognition involves comparing two signals, such as fingerprint images, to determine the probability that they originated from the same source (i.e., individual). The pronounced need for large-scale automated human recognition systems has resulted in the incorporation of biometric solutions in border security systems (e.g., US-VISIT program), access control applications (e.g., laptops), criminal investigations (e.g., AFIS), time-and-attendance technology (e.g., hand geometry readers) and national ID cards (e.g., Hong Kong SmartID). The ascent of biometrics over the past decade belies its humble beginnings in the late 19th century, when the technology was confined to the use of manually recorded human anthropometric measurements for identifying recidivists. Advances in the field of sensor manufacturing, signal processing, pattern recognition, computer vision and machine learning have led to the design of elegant biometric systems that can rapidly establish identity albeit with a few errors.

In the current biometric literature, issues related to biometric data security, privacy, system scalability, database indexing, sensor interoperability and recognition in non-ideal unconstrained environments have been emphasized. This talk will examine the recent progress made in biometrics and discuss some of the interesting problems being addressed by researchers in this field.

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