Real-time detection of face and iris
Chai, Tong Yuen
Mohamed Rizon, Mohamed Juhari, Prof. Dr.
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In this study, a computational algorithm has been developed to automatically detect human face and irises from color images captured by real-time camera. Haar cascade-based algorithm has been applied for simple and fast face detection. The face image is then converted into grayscale image. Three types of image processing techniques have been tested respectively to study its effect on the performance of iris detection algorithm. Then, iris candidates are extracted from the valley created at the face region. The iris candidates are paired up and the cost of each possible pairing is computed by a combination of mathematical models. Finally, the positions of the detected irises are used as a reference to refine the face region. The algorithm has been tested by quality images from Logitech camera and noisy images from Voxx CCD camera. The proposed algorithm has achieved 83.60% as the highest success rate of iris detection under a user-friendly and unconstraint office environment.