An Improved Face Recognition System Using PCA and KNN
In this paper, we improve a face recognition system using Principal Component Analysis (PCA) to extract features from the face images and reduce the dimensionality of each image and K nearest neighbor to classify data. Both methods have been used together to have the most accuracy. Experiments have been carried on Olivetti Research Laboratory Human Face Database (ORL). Face images are in grayscale and in different poses. Results that have been calculated and shown in the last section, illustrates the improvement of our proposed method.
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.