IDENTIFICATION OF FRONT-VIEW FACIAL IMAGES BASED ON ISODENSITY MAPS

In this paper, we describe a method for identifying facial images based on isodensity maps. An isodensity map reflects the 3D shape of the face in sets of closed loops that represent the connectivity of pixels with the same gray level and is a useful feature in facial descriptions. Identification begins by extracting the face region from the source image, then is followed by matching. The extraction of the face region is easily implemented using isodensity lines that represent facial contours. Two-stage matching composed of template matching of isodensity maps (global matching) and local density matching of isodensity lines (fine matching) was adopted. Matching tests were performed on images of faces which included people wearing eyeglasses, women wearing makeup, and unshaven men. A total of 3,481 pairs (59 pairs of the same person and 3,422 pairs of different people) were used and 3,479 (99.9%, 57 pairs of the same person and 3,422 pairs of different people) were correctly identified. The experimental results demonstrated that this is an extremely effective method for personal identification and is sufficiently robust in practical use.