郭艾侠,熊俊涛,肖德琴,邹湘军.融合Harris与SIFT算法的荔枝采摘点计算与立体匹配[J].农业机械学报,2015,46(12):11-17.
Guo Aixia,Xiong Juntao,Xiao Deqin,Zou Xiangjun.Computation of Picking Point of Litchi and Its Binocular Stereo Matching Based on Combined Algorithms of Harris and SIFT[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(12):11-17.
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融合Harris与SIFT算法的荔枝采摘点计算与立体匹配   [下载全文]
Computation of Picking Point of Litchi and Its Binocular Stereo Matching Based on Combined Algorithms of Harris and SIFT   [Download Pdf][in English]
投稿时间:2015-10-10  
DOI:10.6041/j.issn.1000-1298.2015.12.002
中文关键词:  荔枝收获机器人  立体匹配  Harris算法  SIFT算法
基金项目: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)和广东省科技计划“三区”人才资助项目(2015A020224034)
作者单位
郭艾侠 华南农业大学 
熊俊涛 华南农业大学 
肖德琴 华南农业大学 
邹湘军 华南农业大学 
中文摘要: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。
Guo Aixia  Xiong Juntao  Xiao Deqin  Zou Xiangjun
South China Agricultural University,South China Agricultural University,South China Agricultural University and South China Agricultural University
Key Words:Litchi harvesting robots  Stereo matching  Harris algorithm  SIFT algorithm
Abstract: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 of 89.55%, which means that the scheme can improve the computation precision of picking point from main fruit-bearing branch with complex construction.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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