TY - CONF T1 - Recognition of quantized still face images T2 - Biometrics: Theory, Applications, and Systems, 2009. BTAS '09. IEEE 3rd International Conference on Y1 - 2009 A1 - Tao Wu A1 - Chellapa, Rama KW - (signal); KW - algorithm;grey KW - algorithms;face KW - analysis;quantisation KW - analysis;quantized KW - Box-Cox KW - bunch KW - component KW - discriminant KW - exemplar KW - Face KW - FR KW - graph KW - images;distance KW - images;face KW - levels;multiple KW - MATCHING KW - recognition KW - recognition;principal KW - transforms;document KW - transforms;PCA;binary KW - understanding;elastic AB - In applications such as document understanding, only binary face images may be available as inputs to a face recognition (FR) algorithm. In this paper, we investigate the effects of the number of grey levels on PCA, multiple exemplar discriminant analysis (MEDA) and the elastic bunch graph matching (EBGM) FR algorithms. The inputs to these FR algorithms are quantized images (binary images or images with small number of grey levels) modified by distance and Box-Cox transforms. The performances of PCA and MEDA algorithms are at 87.66% for images in FRGC version 1 experiment 1 after they are thresholded and transformed while the EBGM algorithm achieves only 37.5%. In many document understanding applications, it is also required to verify a degraded low-quality image against a high-quality image, both of which are from the same source. For this problem, the performances of PCA and MEDA are stable when the images were degraded by noise, downsampling or different thresholding parameters. JA - Biometrics: Theory, Applications, and Systems, 2009. BTAS '09. IEEE 3rd International Conference on M3 - 10.1109/BTAS.2009.5339030 ER -