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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 (2026). Two-Dimensional PCA for Face Recognition (https://www.mathworks.com/matlabcentral/fileexchange/69377-two-dimensional-pca-for-face-recognition), MATLAB Central File Exchange. Retrieved .
Categories
Find more on Dimensionality Reduction and Feature Extraction in Help Center and MATLAB Answers
General Information
- Version 1.0.0 (3.45 MB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
