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The Bovine Iris Location Method Based on Dynamic Contour Tracking and Least Square Principle
Zhongliang Luo,Yingbiao Jia 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.7
Bovine iris recognition technology plays a very important role in meat food traceability system about large-scale livestock individual identification. In order to improve the precision and speed of bovine iris location, iris inner and outer edge location method based on dynamic contour tracking and least square principle ellipse fitting were respectively proposed in the paper, according to the characteristics of bovine iris image. For iris inner edge location, firstly, the pupil centroid was determined, and pupil sub-image was separated from eye image, then, using dynamic contour tracking method based on the non-initialized level set model to track the boundary of pupil, and got iris inner boundary. For iris outer edge location, noise reducing template was determined by pupil sub-image, which combined with mathematical morphology operators to further suppress random noise, so, ideal outer edge detection curve was obtained. Finally, it got iris outer edge of ellipse fitting based on least squares principle. Experimental results shown that this method was less running time, high location accuracy, it has a certain practicality in large-scale livestock meat food traceability.