Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images

<table>Biometric eigeniris feature information computed for 327 iris features. The <svg height="9.8625002" id="M137" style="vertical-align:-2.29482pt" version="1.1" viewbox="0 0 7.875 9.8625002" width="7.875" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,9.8625)">
<g transform="translate(72,-64.11)">
<text transform="matrix(1,0,0,-1,-71.95,66.45)">
<tspan style="font-size: 12.50px; " x="0" y="0">𝑦</tspan>
</text>
</g>
</g>
</svg>-axis represents the biometric information for each feature (in bits), and the <svg height="7.1624999" id="M138" style="vertical-align:-0.11285pt" version="1.1" viewbox="0 0 8.7250004 7.1624999" width="8.7250004" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,7.1625)">
<g transform="translate(72,-66.27)">
<text transform="matrix(1,0,0,-1,-71.95,66.44)">
<tspan style="font-size: 12.50px; " x="0" y="0">𝑥</tspan>
</text>
</g>
</g>
</svg>-axis is the feature number. The standard deviation is also plotted at the bottom of each graph.</table>

Journal of Electrical and Computer Engineering

fig3

Figure 3

Figure 3: Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images 