关键词: 机器人, 重叠果实, 苹果, K-means, 角点检测, Y型节点, DLS, 轮廓重建

Abstract: In order to improve the precision of apple detection and further increase the work efficiency of apple operation robot, this paper studied  the detecting method with double apples overlapping target under natural environment. Firstly, the region of apple objects in image was extracted by using K-means clustering algorithm under Lab colour space transforming from RGB colour space. Secondly, the key corner points on the apple outline were found among the Harris corner points by calculating the extremum of distance curve between every corner point and the centroid of the overlapped fruits. Then the contour of unblocked apple in overlapped area was extracted by utilizing the Canny algorithm in the detecting window located by key corner points. Thirdly, Y-junctions detection algorithm was utilized to separate contour of individual apple from overlapped apples, and then the complete contour of unblocked apple was obtained. Finally, the missing contour of partly blocked apple was reconstructed by using distance least square algorithm. In order to verify the validity of this method, the Hough transformation method and Spline interpolation method were used to compare with the proposed method for overlapping apples detection. The experimental results showed that the proposed method could not only detect the complete contour of unblocked apple, but also preferably reconstruct the missing contour of partly blocked apple. The average coincidence degree and average error of proposed method were 95.43% and 4.44%, respectively, and its detecting performance was better than that of the former 2 methods, indicating that the proposed method could better detecting double apples overlapping targets under natural environment. Above results  provided reference for automatic detection of apple operation robot with multiple fruits overlapping targets.

Key words: robot, overlapping fruits, apple, K-means, corner point detection, Y-junctions, DLS, contour reconstruction