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)          
© 2016 by IJCTT Journal
Volume-42 Number-1
Year of Publication : 2016
Authors : K Sarath, G. Sreenivasulu
DOI :  10.14445/22312803/IJCTT-V42P106


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. 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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Local Binary Pattern (LBP), Independent Component Analysis (ICA), Sparse Representation, MRLSR, KNN.