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Two-Dimensional PCA for Face Recognition

version 1.0.0 (3.45 MB) by Falah Alsaqre
Implementation of classical Two-Dimensional Principal Component Analysis (2DPCA) for face recognition.

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Updated 08 Nov 2018

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This script implements classical Two-Dimensional Principal Component Analysis (2DPCA) for face recognition. I used simple statements to ease the understanding of 2DPCA-based face recognition. This script is useful for students and researches in this field. The employed dataset is ORL AT&T Laboratories Cambridge (www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces.zip), and it is provided here as mat format (ORL_FaceDataSet).

Cite As

Falah Alsaqre (2018). Two-Dimensional PCA for Face Recognition (https://www.mathworks.com/matlabcentral/fileexchange/69377-two-dimensional-pca-for-face-recognition), MATLAB Central File Exchange. Retrieved .

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MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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