Eye Detection Using Gradient Histogram Matching for Cornea Localization in Refractive Eye Surgery

摘要

In refractive eye surgery using laser, automatically localizing a target eye for surgery and precisely focusing the laser to the corneal surface are crucial to the medical treatment. We therefore propose a new eye detection method based on template matching for automatic localizations of target eyes for refractive eye surgery with excimer laser. In the proposed approach, representative templates of image gradient histograms of eyes are constructed using both open and privately-collected eye datasets. Real-time eye detection that helps guiding the excimer laser to a target eye for surgery can be achieved by the efficient template matching. After the eye localization, image-guided, automatic alignment of positioning marker, i.e., a read line of visible light, is then employed to measure the distance between the corneal surface and the excimer laser. Experimental results show that the proposed eye detection method using template matching outperforms an HoG-based eye detector in miss detection rates based on the same training data for this specific medical application. Also, with the automatic image-guided positioning of laser head, the time consuming process of manual laser focusing can be largely simplified.