Articles published in IJEER

Face Recognition using PCA and LDA Technique for Noisy Faces

Face recognition is always a popular area of research. There are various techniques used in the face recognition system. Principal component analysis (PCA) and linear discriminate analysis (LDA) techniques are the two most well-known techniques for the face recognition. In this paper, the PCA and LDA technique based face recognition system are described. The performance of this technique is compare in term of PSNR and RMSE for noisy image. The Euclidean distance between feature templates and database futures are used for identifying the face image. There are basically three types of noises present, but in this paper I am going to compare the salt and pepper noise with the Gaussian noise in the detailed and analytical ways. After finding the features of the different noisy images I am going to compare both the PCA and LDA technique for the noisy pictures.

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