Iris Texture Description Using Ordinal Co-occurrence Matrix Features

Feature extraction is one of the fundamental steps of any biometric recognition system. The biometric iris recognition is not an exception. In the last 30 years a lot of algorithms have been proposed seeking a better description of the texture image of the human iris. The problem still remains into find features that are robust to the different conditions in which the iris images are captured. This paper proposes a new iris texture description based on ordinal co-occurrence matrix features for iris recognition scheme that increases the recognition accuracy. The novelty of this work is the new strategy in applying robust feature extraction method for texture description in iris recognition. The experiments with the Casia-Interval, Casia-Thousands and Ubiris-v1 databases show that our scheme increases the recognition accuracy and it is robust to different condition of image capture.