Face Recognition Using Markov Stationary Features and Vector Quantization Histogram
Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi · 2014
We have proposed a very simple yet highly reliable face recognition algorithm using VQ histogram. This histogram, obtained by Vector Quantization (VQ) processing for the facial image, is utilized as a very effective personal feature. In this paper, we combine the VQ histogram with Markov Stationary Features (MSF) so as to add spatial structure information to histogram. Experimental results show maximum average recognition rate of 96.16% is obtained for 400 images of 40 persons from the publicly available face database of AT&T Laboratories Cambridge.