Genetic-Based Selection and Weighting for LBP, oLBP, and Eigenface Feature Extraction

In this paper, we have investigated the use of genetic-based feature selection (GEFeS), genetic-based feature weighting (GEFeW) on feature sets obtained by Eigenface and LBP. Our results indicate that GEFeS and GEFeW enhances the overall performance of both the Eigenface and LBP-based techniques. Compared to Eigenface hybrid, our result shows that both LBP and oLBP hybrids perform better in terms of accuracy. In addition, the results show that GEFeS reduces the number of features needed by approximately 50% while obtaining a significant improvement in accuracy. Keywords— Local Binary Pattern (LBP), Eigenface, Steady State Genetic Algorithm (SSGA), Overlapping Patches, Feature Selection.

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