Morphology based non ideal iris recognition using decision tree classifier

With the technological advancement security lapse is of major concern. Hence different techniques are adopted to provide better security. In this juncture, biometrics is widely used. Iris is one of such biometric which can provide high security when compared to other existing biometric traits. In this paper we propose a novel segmentation method for segmenting the iris part which is occluded and can be seen partially. Proposed segmentation has resulted in 90% accurate segmentation over MMU Iris database and with 1.8 seconds time for segmenting each iris. Further different features are extracted from the segmented iris part and are combined to form a feature vector. These are classified using decision tree classifier. Results show improved performance when compared to the existing techniques.