Improved recognition performance with LDA and ICA using vertically and horizontally partitioned facial images

Authors:
Önsen Toygar;Adnan Acan
Affiliations:
Computer Engineering Department, Eastern Mediterranean University, Gazimagusa, Mersin, Turkey;Computer Engineering Department, Eastern Mediterranean University, Gazimagusa, Mersin, Turkey
Venue:
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
Year:
2005

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Abstract

A comparative recognition performance of LDA- and ICA-based multiple classifier systems for face recognition is presented using vertically and horizontally partitioned facial images. A face image is partitioned into several vertical and horizontal segments and a multiple classifier based divide-and-conquer approach is used to combine these segments to recognize the whole face. The experiments demonstrate that vertical and horizontal partitioning result in a better recognition performance compared to the performance results of the holistic methods.