Corneal arcus segmentation method in eyes opened naturally

Abstract

Detection of the corneal arcus by image analysis has important significance for the disintegration of the abnormal lipid metabolism. The traditional method is accompanied with the problem of robustness when the image is collected by non-invasive way. In this paper, an improved corneal arcus segmentation method is proposed. Firstly, locate the candidate area by detecting the eyelid and eyelash. Secondly, on the definition of similarity and the projection of color components, the Union-Find algorithm is used to accomplish the clustering of the target. Finally, the color metrics is defined to complete the segmentation of the corneal arcus. 1968 images from our database are analyzed segmentation accuracy reaches 95.4 % respectively.