Recognition Method of Peaches Growth Morphology in Natural Scene

In order to pick peaches accurately during the tedious process of harvesting, a recognition method of peaches growth morphology in natural scene method is put forward for robot. In five color spaces, such as H, Cr(YCgCr), Cr(YCbCr), R-G, 2R-G and Cb-Cr, a color combination that has the lowest recognition error rate is found out based on BP neural network and the improved K-means clustering algorithm is used to segment image. According to peach morphology features, such as complexity, elongation, eccentricity, etc., the peach growth morphologies are classfied with support vector machine. Experiment results show that the recognition rate of pictures taken in fine day arrives at 87.5%, and the recognition rate of pictures taken in cloudy day reaches to 80.5%. The results show that the proposed method is practical.