Research Article
A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction
Table 2
Average recognition rates and standard deviation on the extended Yale B face database for sample numbers per class
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| Algorithm (feature dim.) | | | | |
| LPP | 63.75 (12.08) | 81.88 (9.86) | 84.37 (7.10) | 90.51 (5.67) | TSA | 46.45 (14.13) | 57.68 (17.40) | 59.35 (15.84) | 56.10 (10.41) | KPCA () | 34.03 (9.23) | 35.85 (9.10) | 38.85 (7.36) | 37.83 (6.10) | KLDA () | 54.70 (12.48) | 73.18 (12.6) | 84.55 (9.40) | 89.17 (8.41) | 2DLDA () | 46.96 (8.72) | 56.87 (7.27) | 65.11 (6.18) | 63.71 (5.02) | LLD () | 30.11 (7.96) | 36.58 (11.33) | 38.26 (9.29) | 39.38 (8.95) | FIFDA () | 26.23 (3.78) | 28.85 (3.98) | 30.91 (2.04) | 35.44 (3.08) | LBMMC | 38.21 (8.72) | 37.12 (10.27) | 45.43 (9.71) | 47.86 (6.79) | 2D-MMC () | 42.00 (9.07) | 48.26 (11.44) | 54.89 (8.99) | 56.92 (9.17) | B2D-MMC () | 33.36 (8.04) | 40.66 (8.35) | 40.32 (8.52) | 42.93 (6.26) | FKMMC () | 60.63 (12.63) | 76.53 (9.77) | 84.92 (6.29) | 90.91 (5.05) |
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