@inproceedings{bd1a21e7d76a42439285c712da27d03a,
title = "Improved methods on PCA based human face recognition for distorted images",
abstract = "This paper examines various illumination invariant techniques and identifies the one which works well with principle component analysis for human face recognition. Experimental results show that by applying the technique called Gradientfaces at the pre-processing stage which computes the orientation of the image gradients in each pixel of the face images and uses the computed face representation as an illumination invariant version of the input image, it can greatly improve the recognition rates. From a low recognition rate of 6.25\% up to 60.75\% testing on the Asian face database which has images with various illumination.",
keywords = "Face recognition, Gradientfaces, Illumination insensitive measure, Principle component analysis (PCA)",
author = "Bruce Poon and Amin, \{M. Ashraful\} and Hong Yan",
year = "2016",
language = "English",
isbn = "9789881925381",
volume = "1",
publisher = "Newswood Limited",
pages = "339--344",
booktitle = "Lecture Notes in Engineering and Computer Science",
note = "International Multiconference of Engineers and Computer Scientists 2016, IMECS 2016 ; Conference date: 16-03-2016 Through 18-03-2016",
}