A Study on Pupil and Iris Segmentation of the Anterior Segment of the Eye
Ho Chul Kang, Kwang Gi Kim, Whi-Vin Oh, Jeong‐Min Hwang · Journal of Korean Society of Medical Informatics · 2009
Objective: The goal of this study was to develop a novel pupil and iris segmentation algorithm.We evaluated segmentation performance based on a fractal model.Two methods were compared: Daugman's and our new proposed method.Methods:We received 200 anterior segment images with 3,872×2,592 pixels.Here we present an active contour model that accurately detects pupil boundaries in order to improve the performance of segmentation systems.We propose a method that uses iris segmentation based on a fractal model.We compared the performance of Daugman's method and the proposed new method and statistically analyzed the results.Results: We manually compared segmentation with the Daugman's method and the new proposed method.The findings showed that the proposed segmentation accuracy was about 2.5 percent higher than Daugman's method.There was a significant difference (p<0.05) between the under and over data between the two methods. Conclusion:The results of this study show that the new proposed method was more accurate than the conventional method for the measurement of segmentation of the eye by CAD (Computer-aided Diagnosis).(