The research of glasses removal based on PCA/ICA and error compensation
Liu Zhong-mi · Optical Technique · 2014
Glasses as the most common occluding object in facial images have a greatly influence on face recognition performance.In order to improve the recognition rate with glasses,the glasses need to be removed from frontal facial image.An algorithm based on principle component analysis and independent component analysis is proposed to extract the second order statistics feature and higher-order information,which depicting well the detailed features of a face.Gray compensating algorithm is adopted in order to remedy distortion,for which the image that wear glasses do not participate in the training of the feature space.Iterative compensation algorithm is used for face reconstruction.The simulation experimental results show that through the Yale face database,the synthesize images using the proposed method have not the signs of glasses,looks more natural,improve effectively the characteristics of face images with glasses and face recognition rate.