Human face recognition using a spatially weighted modified Hausdorff distance

Hausdorff distance is an efficient measure of the similarity of two point sets. We propose a modified Hausdorff distance measure for human face recognition. This modified Hausdorff distance measure incorporates information about the location of important facial features when comparing the edge maps of two facial images. The distance measure is weighted according to a weighted function derived from the spatial information of the human face. This distance measure, namely spatially weighted Hausdorff distance (SWHD), is further improved by combining it with the `doubly´ modified Hausdorff distance (M2HD). This new Hausdorff distance measure is called spatially weighted `doubly´ Hausdorff distance (SW2HD), which can alleviate the effect of facial expressions in human face recognition. Experiment results show that both the SWHD and SW2HD outperform the M2HD in recognition rate. The SW2HD can achieve the best recognition rate among the different Hausdorff distance measures. In our experiment, its recognition rates are 89%, 94%, and 98% for the first one, the first five, and the first ten likely matched faces, respectively. The average processing time for recognition of a human face is less than one second