A Gabor-Block-Based Kernel Discriminative Common Vector Approach Using Cosine Kernels for Human Face Recognition

<div class="floats-full-page floats-full-page-other"><h2>Table 6</h2><div class="floats-full-page-caption">Comparison of recognition accuracy of various methods with the proposed method.</div><div class="floats-full-page-content"><table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr /></td></tr><tr class="thead"><td align="left">Method</td><td align="center">Highest recognition accuracy</td></tr><tr><td class="thead-hr" colspan="2"><hr /></td></tr><tr><td align="left">GDA</td><td align="center">78.04%</td></tr><tr><td align="left">Elastic graph matching (EGM) [<a href="../../421032/#B9">9</a>]</td><td align="center">80.00%</td></tr><tr><td align="left">DCT-LDA</td><td align="center">80.87%</td></tr><tr><td align="left">GWT</td><td align="center">81.1%</td></tr><tr><td align="left">DCT-GDA</td><td align="center">82.84%,</td></tr><tr><td align="left">GWT-LDA</td><td align="center">84.1%</td></tr><tr><td align="left">DCT-KDCV</td><td align="center">85.13%</td></tr><tr><td align="left">Gabor fusion KDCV</td><td align="center">&#13;
									91.22%</td></tr><tr><td align="left">Proposed approach</td><td align="center"><b>94.25%</b></td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr" /></td></tr></table></td></tr></table></div></div>

Table 6 | A Gabor-Block-Based Kernel Discriminative Common Vector Approach Using Cosine Kernels for Human Face Recognition

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Table 6: A Gabor-Block-Based Kernel Discriminative Common Vector Approach Using Cosine Kernels for Human Face Recognition

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Table 6

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