Low Computational Iris Recognition Based on Moving Average Filter

A moving average filter averages a number of input samples and produce a single output sample. This averaging action removes the high frequency components present in the signal. Moving average filters are normally used as low pass filters. In recursive filtering algorithm, previous output samples also are taken for averaging. This is the reason why it's impulse response extends to infinity. We have developed a low computational approach for iris recognition based on 1D moving average filter. Simple averaging is used to reduce the effects of noise and a significative improvement in computational efficiency can be achieved if we perform the calculation of the mean in a recursive fashion.
LicenseFree
File Size53.4 kB
Version1.0
Operating System Windows Vista Windows XP Windows 2000 Windows Me Windows NT Windows 95 Windows 98 Windows Server 2008 Windows 3.x Windows Windows 2003
System RequirementsMatlab 7.0