Multi-unit Iris Recognition System by Image Check Algorithm

In this paper, we propose the iris recognition system, which can select the good quality data between left and right eye images of same person. Although iris recognition system has achieved good performance, but it is affected by the quality of input images. So, eye image check algorithm, which can select the good quality image is very important. The proposed system is composed of four steps. At the first step, both eye images are captured at the same time. At the second step, the eye image check algorithm picks out noisy and counterfeit data between both eye images and offer a good qualified image to the next step. At the third step, Daubechies’ Wavelet is used as a feature extraction method. Finally, Support Vector Machines(SVM) and Euclidian distance are used as classification methods. Experiment results involve 1694 eye images of 111 different people and the best accuracy rate of 99.1%.

• Type: Conference
• Year: 2004
• Where: ICBA
• Authors: Jain Jang, Kang Ryoung Park, Jinho Son, Yillbyung Lee
• Keywords: Biometrics, Eye Image Check, Eye Images, ICBA 2004, Image Check Algorithm