A system capable of pattern matching between a less noisy face image and a noisier face image obtained in different imaging conditions. A weighted sum of a covariance matrix calculated from less noisy sample images obtained for a plurality of sample faces and a covariance matrix calculated from differences between the less noisy sample images and corresponding noisier sample images obtained for the sample faces is first obtained. A principal component analysis is applied to the weighted sum to find and store in memory a result with which principal components are calculated from a given face image. In actual pattern matching, a first face image and a second face image are first obtained. The degree of similarity between the first and second face images is calculated based on a conventional formula by using the result of the principal component analysis. The matching between the first and second face images is achieved based on a comparison of the degree of similarity with a predetermined threshold value.
Face recognition-matching system effective to images obtained in different imaging conditions