We have developed a very simple yet highly reliable face recognition method called VQ histogram method. Codevector referred (or matched) count histogram, which is obtained by Vector Quantization (VQ) processing of facial image, is utilized as a very effective personal feature value. In our work, for utilizing the position information of the face, furthermore, a region-division VQ histogram method is proposed in this paper. We divide the facial area into 5 regions of facial parts (forehead, eye, nose, mouth, jaw), recognition results with different parts are first obtained separately and then combined by weighted averaging. Topi recognition rate of 97.4% is obtained by using FB task (1195 images) of the standard FERET database. Based on VQ histogram method, moreover, we also have developed simple face recognition method called Adjacent Pixel Intensity Difference Quantization (APIDQ) Histogram Method, which is much simpler and has equivalent performance in feature extraction as compared with the former. By utilizing the table look-up (TLU) method in the quantization step, the total recognition processing time is reduced to only 147 msec.