Extraction and Recognition of Nonlinear Interval-Type Features Using Symbolic KDA Algorithm with Application to Face Recognition

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left"></td><td align="left">Kernel Eigenface</td><td align="left">Symbolic KDA</td><td align="left">Kernel Fisherface</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">Polynomial
 kernel</td><td align="left">55.61</td><td align="left">91.86</td><td align="left">84.95</td></tr><tr><td align="left">Gaussian
 kernel</td><td align="left">58.05</td><td align="left">89.39</td><td align="left">81.57</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Comparison of symbolic KDA method using optimal parameters.

Journal of Electrical and Computer Engineering

tab3

Table 2

Table 2: Extraction and Recognition of Nonlinear Interval-Type Features Using Symbolic KDA Algorithm with Application to Face Recognition 