-->PCA-for dimensionality reduction.
-->LBP- it's efficient in the illumination, rotation, and grayscale variance
-->WHT- Walsh-Hadamard Transform(WHT) for orthogonal transformation is used for feature extraction. Before applying LBP here I applied the first Walsh-Hadamard Transform (WHT) for orthogonal transformation.
To learn more about the background of the dataset, and the AIFR you must visit the : https://scholar.google.com/scholar?cluster=3626589220394005192&hl=en&as_sdt=2005
Patel, P., and A. Ganatra. "Investigate age invariant face recognition using PCA, LBP, Walsh Hadamard transform with a neural network." International Conference on Signal and Speech Processing (ICSSP-14). 2014. ##BibTex @inproceedings{patel2014investigate, title={Investigate age invariant face recognition using PCA, LBP, Walsh Hadamard transform with neural network}, author={Patel, P and Ganatra, A}, booktitle={International Conference on Signal and Speech Processing (ICSSP-14)}, pages={266--274}, year={2014} }