2D Face Recognition Based on PCA & Comparison of Manhattan Distance, Euclidean Distance & Chebychev Distance
نویسندگان
چکیده
This paper is about human face recognition in image files. Face recognition involves matching a given image with the database of images and identifying the image that it resembles the most. Here, face recognition is done using: (a) Eigen faces and (b) Applying Principal Component Analysis (PCA) on image. The aim is to successfully demonstrate the human face recognition using Principal component analysis & comparison of Manhattan distance, Euclidean distance & Chebychev distance for face matching. KeywordsEigenfaces, Eigenvector, Eigenvalue , PCA, Multiview, Euclidean distance, Chebychev distance, Manhattan distance.
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