Subscription or Fee Access
A Face Recognition Scheme Based on Weighted Face Features and Wavelet Transform
In face recognition, face feature extraction and reduction of the dimensions is the key question to face recognition. The face recognition algorithm is based on wavelet transform only in the low-frequency component of the wavelet decomposition to extract image features for classification. The results have a lot of parts of the high-frequency components to identify favorable information. In order to extract more effectively facial image features, the proposed face recognition algorithm is based on wavelet transform and feature weighting fusion. Firstly, wavelet transform can reduce the dimension of the human face images. Four wavelet sub-bands have respectively extract features using principal component analysis (PCA) and feature weighted fusion. Finally, the use of support vector machine (SVM) classification is important. The experiments on the ORL database and the recognition accurate rate can reach 98.50%. The experiment results are shown that the algorithm can effectively improve the face recognition ability, it is compared with traditional recognition algorithm has high recognition accuracy and recognition speed.
Wavelet Transform, Principal Component Analysis, Weighted Fusion, Support Vector Machines, Face Recognition.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.