Research on branches recognition of apple harvesting robot

Branches recognition of apple harvesting robot were studied to provide rich environment information for robot's harvesting obstacle avoidance. Firstly, the leaves and other background in the apple image were removed based on R-G color difference. Secondly, image segmentation was conducted using K-Means clustering based on “a” color feature in the Lab color space. Then the noise removal and image perfection operation were executed, and the central axis - the main characteristics of branches - was extracted through skeletonizing method and removing subbranch method. Finally, experiments were carried out on recognition of apple branches, indicating feasibility and effectiveness of the proposed method.