Face recognition approach based on rank correlation of Gabor-filtered images

✍ Scribed by Olugbenga Ayinde; Yee-Hong Yang

• Publisher: Elsevier Science
• Year: 2002
• Tongue: English
• Weight: 394 KB
• Volume: 35
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(01)00120-0

✦ Synopsis

Face recognition is challenging because variations can be introduced to the pattern of a face by varying pose, lighting, scale, and expression. A new face recognition approach using rank correlation of Gabor-ÿltered images is presented. Using this technique, Gabor ÿlters of di erent sizes and orientations are applied on images before using rank correlation for matching the face representation. The representation used for each face is computed from the Gabor-ÿltered images and the original image. Although training requires a fairly substantial length of time, the computation time required for recognition is very short. Recognition rates ranging between 83.5% and 96% are obtained using the AT&T (formerly ORL) database using di erent permutations of 5 and 9 training images per subject. In addition, the e ect of pose variation on the recognition system is systematically determined using images from the UMIST database.