A gradient-based face recognition method using Partial Hausdorff Distance (PHD) measure is proposed in this paper.
First, in order to achieve a performance independent of lighting conditions, the image is transformed into a Gradient Map
(GM). And then, Hausdorff distance measure is introduced to calculate the dissimilarity between two Gradient Maps. The
experimental data show that the measure is suitable for face recognition. As we can see later, this distance measure is
robust to lighting variations, slight pose differences and expression changes in face images. At last, recognition accuracy
is given tested on AR and FERET databases, and comparisons with Edge Map (EM) and Line segment Edge Map (LEM)
approaches are also presented.