We are showing the Results of the PCA+SVD based face Reorganization. As we can see , we give the input sample image and at the output we get the matched images from the large image data set by use PCA+SVD .
Figure 5 :- Face Reorganization by PCA +SVD Figure 6 is showing the output of the Accuracy . As we can see from the figure 6 the accuracy of the PCA+SVD is high as compare to PCA . Green color graph is showing the Accuracy for the PCA while Black color is showing the accuracy for the PCA+SVD based face reorganization.
In this paper, we are improving the accuracy of the face reorganization system . In the previous paper , they was using PCA algorithm for face detection . In this thesis, we are using PCA +SVD based algorithm so that accuracy can get increase .As we can see from the results session , the Accuracy of PCA+SVD get increase up to 30% as compare to PCA.
In the future ,we can work for the project limitations. According to our first limitation , in the future we can work for the Face expression also . In the present time we are working only for the Face Recognition but face expression recognition system also can be introduce along with Face recognition. In the results session ,we can also introduce some more parameters like PSNR and MSE . We can also introduce the hardware for detect the face and also able to increase the data base .
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