关键词: 眼底图像, 硬性渗出物, 引力搜索, 蜻蜓算法, 随机森林算法

Abstract: Accurately identifying the location of hard exudate in retinal fundus helps to reduce the risk of blindness caused by diabetic retinopathy. An approach based on IDA-RF is proposed for hard exudate detection. It needs to pretreat the fund image and then extract the exudate candidate region, which using the [k]-means clustering to initialize the population. Meanwhile, combining with the universal gravitation search algorithm, constantly updating the step formula, an Improved Dragonfly Algorithm（IDA） is proposed. IDA optimizes the parameters for the random forest algorithm in the optimization process, classifies the exudate region by using the optimized random forest algorithm, which aims to extract the position of the final hard exudate. This method is tested in a public fundus image database, compared with RF, DA-RF and GSA-RF, the accuracy of hard exudate is 97.28%. The experiments show that this method can accurately identify the hard exudates and has good robust performance.

Key words: fundus image, hard exudate, gravitational search, dragonfly algorithm, random forest algorithm