Performance study of Face Recognition systems using LBP and ICA descriptors with sparse representation - MRLSR and KNN Classifiers, respectively
K Sarath, G. Sreenivasulu "Performance study of Face Recognition systems using LBP and ICA descriptors with sparse representation - MRLSR and KNN Classifiers, respectively". International Journal of Computer Trends and Technology (IJCTT) V42(1):33-41, December 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
In this paper an attempt has been to study and
compare the results of two scenarios, i.e. 1) LBP
descriptor with sparse representation (MRSLR)
classifier and 2) ICA descriptor with KNN classifier, of
a face recognition system, on a standard image data sets
for training and testing with/without noise, occultation
and different illumination facial images. The results
show that the second scenario ICA + KNN exhibits
better performance, compared to the first scenario LBP
+ MRSLR as descriptors and classifiers, respectively.
The results show that the ICA + KNN scenario exhibits
better performance, with a faster recognition speed and
more recognition accuracy.
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Keywords
Local Binary Pattern (LBP), Independent
Component Analysis (ICA), Sparse Representation,
MRLSR, KNN.