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- W2205397672 abstract "In this paper, we compare the performance of three composite correlation filters in facial recognition problem. We used the ORL (Olivetti Research Laboratory) facial image database to evaluate K-Law, MACE and ASEF filters performance. Simulations results demonstrate that K-Law nonlinear composite filters evidence the best performance in terms of recognition rate (RR) and, false acceptation rate (FAR). As a result, we observe that correlation filters are able to work well even when the facial image contains distortions such as rotation, partial occlusion and different illumination conditions." @default.
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- W2205397672 date "2011-01-01" @default.
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- W2205397672 title "Performance of Correlation Filters in Facial Recognition" @default.
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- W2205397672 doi "https://doi.org/10.1007/978-3-642-21587-2_17" @default.
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