Face image registration methods using Normalized Cross Correlation

In the many processing stage of face recognition, one of the most important parts is face detection. In the recent years, there has been much progress in face detection. Many face recognition system adopt or develop the Adaboost: Viola-Jones face detection system. But the detected face image by adaboost method has serious problems. Face regions are apt to be different at each time, and the detected face image includes the rotated face. These issues give the bad effect to the feature extraction stage of the face recognition. In order to solve these problems, many researchers normalize the scale of face through the detection of detail element of a face, especially the eye detection. Generally, the home service robot mounts the low resolution camera. As the distance between a robot and a user becomes increasing, it is very difficult to obtain the good result by those methods. In this paper, Normalized Cross Correlation is used to detect the exact face region in the low resolution face image. The experiments showed that our method using NCC give the much better face recognition rate.