Comparison of Segmentation Methods for an Accurate Iris Extraction

Biometric identification systems recognize persons by a digital signature derived from a particular physiological attribute. One such attribute is the unique patterns that exist in the texture of an iris. These patterns provide sufficient information to uniquely identify an individual. Segmentation of the iris texture from an acquired digital image is not always accurate the image contains noise elements such as skin, reflection and eyelashes that must be located and removed. We compare and contrast four texture description and two hybrid pattern classification methods for segmenting iris texture using a region based pattern classification approach. These techniques are evaluated by analyzing their segmentation accuracy.