摘要
为了满足荔枝收获机器人对整串果实采摘作业的需求,提出一种融合Harris与SIFT算法的荔枝采摘点计算与立体匹配方案。首先在已识别的荔枝结果母枝部位进行Harris角点检测,结合提取已识别荔枝果实区域质心与最小外接矩形等特征信息,进行采摘点二维像素坐标的计算。然后通过对比分析,提出对计算采摘点采用带约束条件基于余弦相似度的SIFT双目立体匹配,最后进行采摘点计算与双目立体匹配实验验证。结果表明,计算采摘点的匹配成功率可达89.55%,且该方法更能满足在结构复杂的结果母枝上采摘点计算的精度需求。
A vision-based fruit-vegetable picking robot helps to improve picking efficiency by making full use of the information by which the target of harvest can be recognized and located. For harvesting robots,it is important and difficult to calculate and locate the picking point from the recognized main fruit bearing branch of litchi. Hence,calculation of picking point and its stereo match become the research focuses. To meet the needs of picking the whole litchi cluster for litchi picking robot,a scheme of combined algorithms of Harris and improved SIFT to compute picking point of litchi and achieve its stereo matching was proposed. Firstly,corner extraction from the main fruit bearing branch of litchi was carried out by Harris method,and the whole identified area of litchi fruits was taken as a big fruit,the feature information on ＂centroid＂and the maximal vertical coordinate vertex of the MBR（ Minimum bounding rectangle） of the big fruit（ denoted by Y） were then attained. Then,taking each Harris corner whose vertical coordinates were bigger than Y as the center of circle,all possible circles were computed and the center of circle whose circle area was the maximum was chosen as the pixel coordinate of picking point in original collected litchi image. Furthermore, the computed picking point was described with a characteristic vector of SIFT with 128 dimensions,and its binocular stereo matching based on cosine distance similarity of SIFT was also proposed. Theoretical analysis and experimental results show that the proposed scheme can satisfy the need of vision of litchi picking robot with successful matching rate of89. 55%,which means that the scheme can improve the computation precision of picking point from main fruit-bearing branch with complex construction.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2015年第12期11-17,共7页
Transactions of the Chinese Society for Agricultural Machinery
基金
广东省自然科学基金博士科研启动项目(2014A030310275
S2013040015381)
国家星火计划资助项目(2014GA780057)
广东省科技计划'三区'人才资助项目(2015A020224034)
