Real-time iris detection

Authors:
Mohamed Rizon;Chai Tong Yuen;Ali Almejrad;Naif Alajlan
Affiliations:
Department of Biomedical Technology, King Saud University, Riyadh, Kingdom of Saudi Arabia 11433;Department of Mechatronic and Biomedical Engineering, Universiti Tunku Abdul Rahman (UTAR), Kuala Lumpur, Malaysia;Department of Biomedical Technology, King Saud University, Riyadh, Kingdom of Saudi Arabia 11433;Advanced Laboratory for Intelligent Systems Research, Department of Computer Engineering, King Saud University, Riyadh, Kingdom of Saudi Arabia
Venue:
Artificial Life and Robotics
Year:
2010

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Abstract

A real-time algorithm to automatically detect human faces and irises from color images has been developed. A Haar cascade-based algorithm has been applied for simple and fast face detection. The face image is then converted into a gray-scale image. Three types of image processing techniques have been tested to study their effect on the performance of the iris detection algorithm. Then iris candidates are extracted from the valley of the face region. The iris candidates are paired up and the cost of each possible pairing is computed by a combination of mathematical models. The pairing with the lowest cost is considered to be a pair of irises. The algorithm has been tested by quality images from a Logitech camera and noisy images from a Voxx CCD camera. The proposed algorithm has achieved a success rate of 83.60% for iris detection in an open office environment.