Efficient detection of citrus fruits in the tree canopy under variable illumination conditions

摘要

This paper focuses on the detection of citrus fruits in the tree canopy under variable illumination and different degree occlusion. We applied a novel segmentation method to detect the visible parts of fruits by fusing the segmentation results of chromatic aberration map, normalized RGB model, and illumination map. This fusion method can detect the highlights, shadows and diffuse zones of fruit targets. The 3-D surface topography of the visible parts of fruits were recovered by the classical algorithm of shade from shading, the fruit targets were recovered by sphere fitting using these point cloud data, and the valid ones were chosen out by validity check. The results showed that the occlusion zones of targets were effectively recovered under various light conditions integrally using the proposed method.