Detecting citrus fruits and occlusion recovery under natural illumination conditions

Abstract

A method based on color information and contour fragments was developed to identify citrus fruits in variable illumination conditions within tree canopy, in order to guide the robots for harvesting citrus fruits. The color properties of fruit targets within citrus-grove scene were analyzed, a preliminary segmentation method was put forward by fusing the chromatic aberration information and normalized RGB model. The set of contour fragments was constructed by detecting the significant edges of chromatic aberration map and the corners within these edges. The valid subset was chosen out by three indicators of every fragment: length, bending degree, and concavity or convexity. The combination analysis was done for these valid contour fragments, and the ellipse fitting was used for every subset of valid fragments to recover the occluded fruits. The partial order relationship was derived based on the distribution of the edge within the overlapped area. The results showed that occluded fruits were effectively recovered under natural outdoor light conditions using the proposed method, and the relative error was 5.27%. The partial order relation of fruit targets provide key cues for path planning of harvesting robot.