In this paper, a novel face recognition method based on binary face edges is presented to deal with the illumination problem. The Binary Face Edge Map (BFEM) is extracted using the Locally Adaptive Threshold (LAT) algorithm. Based on BEFM, a new image similarity metric is proposed. Experimental results show that face recognition rates of 76.32% and 82.67% are achieved respectively on 798 AR images and 150 Yale images with changed lighting conditions and facial expression variations when one sample per subject is used as the target image. The proposed method takes less time for image matching and outperforms some existing face recognition approaches, especially in changed lighting conditions. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Song, J., Chen, B., Chi, Z., Qiu, X., & Wang, W. (2007). Face recognition based on binary template matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4681 LNCS, pp. 1131–1139). Springer Verlag. https://doi.org/10.1007/978-3-540-74171-8_115
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