Abstract
ABSTRACT Face recognition based on 2D face images is still challenged by the large change of illumination, pose and expression after more than 10 years’ research and its recognition rate is still far away from satisfaction under the change of the above three factors. Gabor wavelet and support vector machine (SVM) are studied. Gabor wavelet has good biological neurons function, and good adaptive change to illumination. Furthermore, SVM can provide good classification effect. Gabor wavelet and SVM are combined with PCAto improve recognition rate of human face. Besides, we put forward a kind of Gabor wavelet feature extraction method based on three-dimensional human face contour line. Five different types of human face recognition are used to verify the effectiveness of this algorithm. The experiment results show that the proposed scheme has higher recognition rate than several traditional schemes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
