  As a stable biometric system, iris has recently attracted great attention
among the researchers. However, research is still needed to provide appropriate
solutions to ensure the resistance of the system against error factors. The
present study has tried to apply a mask to the image so that the unexpected
factors affecting the location of the iris can be removed. So, pupil
localization will be faster and robust. Then to locate the exact location of
the iris, a simple stage of boundary displacement due to the Canny edge
detector has been applied. Then, with searching left and right IRIS edge point,
outer radios of IRIS will be detect. Through the process of extracting the iris
features, it has been sought to obtain the distinctive iris texture features by
using a discrete stationary wavelets transform 2-D (DSWT2). Using DSWT2 tool
and symlet 4 wavelet, distinctive features are extracted. To reduce the
computational cost, the features obtained from the application of the wavelet
have been investigated and a feature selection procedure, using similarity
criteria, has been implemented. Finally, the iris matching has been performed
using a semi-correlation criterion. The accuracy of the proposed method for
localization on CASIA-v1, CASIA-v3 is 99.73%, 98.24% and 97.04%, respectively.
The accuracy of the feature extraction proposed method for CASIA3 iris images
database is 97.82%, which confirms the efficiency of the proposed method.
