  Pattern recognition problem rely upon the features inherent in the pattern of
images. Face detection and recognition is one of the challenging research areas
in the field of computer vision. In this paper, we present a method to identify
skin pixels from still and video images using skin color. Face regions are
identified from this skin pixel region. Facial features such as eyes, nose and
mouth are then located. Faces are recognized from color images using an RBF
based neural network. Unsupervised Cellular Automata with K means clustering
algorithm is used to locate different facial elements. Orientation is corrected
by using eyes. Parameters like inter eye distance, nose length, mouth position,
Discrete Cosine Transform (DCT) coefficients etc. are computed and used for a
Radial Basis Function (RBF) based neural network. This approach reliably works
for face sequence with orientation in head, expressions etc.
