A FEATURE EXTRACTION METHOD FOR PERSONAL IDENTIFICATION SYSTEM BY USING REAL-CODED GENETIC ALGORITHM

摘要

Recently in the world, many researches for individual identification method using biometrics are widely done. Especially, personal identification using faces are used because of needless for physical contact. However, when the number of registrant of a system increase, the recognition accuracy of system will get worse certainly. Therefore, in order to improve recognition accuracy, it is necessary to extract the feature area effective for recognition. In this paper, we analyze and examine about the individual feature in a face using the RGA and the SPCA. Thus, by removing the area which is not valuable, we think that recognition accuracy becomes high. Then, in order to show the effectiveness of the proposed method, we show computer simulations by using real image. From these results, we show the effectiveness.