Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left">Iris image databases <i>↓</i> weights of subregion of annular iris area →</td><td align="center">Upper</td><td align="center">Middle</td><td align="center">Bottom</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">CASIA-V3 Interval</td><td align="center">0.1000</td><td align="center">0.4000</td><td align="center">0.5000</td></tr><tr><td align="left">CASIA-V3 Lamp</td><td align="center">0.2941</td><td align="center">0.5294</td><td align="center">0.1765</td></tr><tr><td align="left">MMU-V1 </td><td align="center">0.7692</td><td align="center">0.0770</td><td align="center">0.1538</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Weighted coefficients assignment on subregion for three databases.

The Scientific World Journal

tab2

Table 2

Table 2: Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion 