  This paper presents face recognition using maximum a posteriori (MAP)
discriminant on YCbCr color space. The YCbCr color space is considered in order
to cover the skin information of face image on the recognition process. The
proposed method is employed to improve the recognition rate and equal error
rate (EER) of the gray scale based face recognition. In this case, the face
features vector consisting of small part of dominant frequency elements which
is extracted by non-blocking DCT is implemented as dimensional reduction of the
raw face images. The matching process between the query face features and the
trained face features is performed using maximum a posteriori (MAP)
discriminant. From the experimental results on data from four face databases
containing 2268 images with 196 classes show that the face recognition YCbCr
color space provide better recognition rate and lesser EER than those of gray
scale based face recognition which improve the first rank of grayscale based
method result by about 4%. However, it requires three times more computation
time than that of grayscale based method.
