Gender Classification of Face Image Based on Kernel Principal Component Analysis plus Canonical Correlation Analysis

The method of kernel principal component analysis plus canonical correlation analysis,its efficiency in extraction,classification and analyses of face features has caught attention for relevant researchers,it can identify directly the sex of a person from a original grayscale face image.Kernel method is used within principal component analysis,since CCA uses all the kernel principal component of the converted samples from KPCA,no discrimination is lost in the analysis,so the robust is higher in the original grayscale face image of variations of illumination,expression,pose and face details.The experiments were conducted with nearest feature classifier based on kernel method in the ORL face database,an average accuracy rate of 96% is achieved.