Modeling and Simulation Research on Gender Recognition Based on Face image
Yang Xian-feng · Jisuanji fangzhen · 2012
Face images are influenced by illumination,pose,age changes and other effects,and it is difficult using a single feature extraction method to obtain high accuracy of sex recognition.In order to improve the correct rate of gender recognition,the geometric characteristics and principal component analysis were combined with the gender recognition algorithm.First,geometric features method was used for face image feature extraction.Then the principal component analyses was use to select the characteristics which have important implications for the identification results.Finally,the characteristics were input to the support vector machine for learning and the gender classifier was established.The Indians face base was used with the algorithm for performance tests.The results show that this algorithm can accelerate the gender recognition speed and improve the correct rate of recognition under larger chang in illumination and pose.