Date:  Friday, September 3, 2010

Seminar 3:30

Place: Duthie Center, Room 117

Reception: 3:00 – 3.30pm, Duthie Center 2^nd Floor

ABSTRACT

A reliable thermal face recognition system can enhance the national security applications such as prevention against terrorism, surveillance, monitoring and tracking, especially at nighttime. In this paper, we present a novel face recognition approach utilizing thermal (long wave infrared) face images that can automatically identify a subject at both daytime and nighttime. With a properly acquired thermal image (as a query image) in monitoring zone, the following processes will be employed: normalization, face detection, face alignment, face masking, Gabor wavelet transform, face pattern words (FPWs) creation, face identification by similarity measure (Hamming distance). Specifically, at each frequency band of GWT, an index number representing the strongest orientational response is selected, and then encoded in binary format to favor the Hamming distance calculation. Multiple-band orientation codes are then organized into a face pattern word by using order statistics. If eyeglasses are present on a subject's face, an eyeglasses mask will be automatically extracted from the querying face image, and then masked with all comparing FPWs (no more transforms) stored in database. A high identification rate (97.75% with Top-1 match) has been achieved upon our preliminary face dataset (of 45 subjects) from the proposed approach regardless operating time and glasses-wearing condition.

Short Bio:<

Yufeng Zheng received his Ph.D. degree in Image Processing from the Tianjin University (Tianjin, China) in 1997. He is presently with the Alcorn State University (Mississippi, USA) as an assistant professor. Dr. Zheng serves as a program director of the Computer Networking and Information Technology Program, and a director of the Pattern Recognition and Image Analysis Lab. He is the principle investigator (PI) of two federal grants and the Co-PI of several grants. So far Dr. Zheng holds two patents in glaucoma classification and face recognition, and has published two book chapters and 35 scientific papers. His research interests focus on image analysis, pattern recognition, visual process modeling, biometrics, and computer-aided diagnosis.