Title: One-sample face recognition with local similarity decisions

Authors: Alex P. James

Addresses: Center for Excellence in Applied Machine Intelligence and Pattern Analysis, The Indian Institute of Information Technology and Management, Kerala, Technopark Campus, Trivandrum 695581, India

Abstract: Inter-class and intra-class variability account for poor classification performance of automatic image recognition methods under the condition of limited number of gallery images per class. Texture-based intensity features in combination with local decisions on similarity measurements are used to reduce the effects of variability and to provide a robust image recognition method. The presented method show good recognition performance when tested under the most difficult condition of using single gallery image per class on AR, YALE , EYALE and FERET 2D face image databases.

Keywords: template matching; threshold; local decisions; face recognition; similarity measurements; gradient filters; robustness; biometrics; automatic image recognition; texture based intensity features; variability.

DOI: 10.1504/IJAPR.2013.052340

International Journal of Applied Pattern Recognition, 2013 Vol.1 No.1, pp.61 - 80

Received: 22 Aug 2012
Accepted: 29 Sep 2012
Published online: 31 Jul 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article