Facial Recognition using Hausdorff- Shape- Radon Transform

This paper proposes a robust method for face recognition with variant illumination, scaling and rotation. Techniques introduced in this work are composed of two stages. First, the feature of face is to be detected by the combined of Trace Transform and Fast Active Contour. Then, in the second stage, the Hausdorff distance and Modified Shape Context are employed to measure and determine of similarity between models and test images. Finally, our method is evaluated with experiments on the AR, ORL and Yale face database using 6,325 face images and compared with other related works (e.g. Eigen face). The extensive experimental results show that the average of accuracy rate of face recognition with variant illumination, scaling and rotation is higher than 84%.