刘继展,朱新新,袁妍.枝上柑橘果实深度球截线识别方法[J].农业机械学报,2017,48(10):32-39.
LIU Jizhan,ZHU Xinxin,YUAN Yan.Depth-sphere Transversal Method for on-branch Citrus Fruit Recognition[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(10):32-39.
摘要点击次数: 1966
全文下载次数: 1116
枝上柑橘果实深度球截线识别方法   [下载全文]
Depth-sphere Transversal Method for on-branch Citrus Fruit Recognition   [Download Pdf][in English]
投稿时间:2017-02-21  
DOI:10.6041/j.issn.1000-1298.2017.10.004
中文关键词:  柑橘  采摘  识别  深度信息  球截线  特征提取
基金项目:国家自然科学基金项目(51475212)、江苏省自然科学基金项目(BK20151339)、江苏省高校自然科学研究重大项目(16KJA210002)和江苏省高校优势学科建设工程项目(PAPD)
作者单位
刘继展 江苏大学 
朱新新 江苏大学 
袁妍 江苏大学 
中文摘要:针对柑橘果、叶、枝对象具有球体、片体和细柱体不同的三维几何特征,提出一种识别柑橘果实的深度球截线方法。首先提出了球形果实特征提取的深度球截线方法的基本原理和关键参数,进而分别针对枝上果、叶孤立和贴碰区域提出了孤立果实的特征提取算法和贴碰果实的特征提取算法,得到了复杂枝环境下的深度数据处理与果实识别策略,并综合根据Intel RealSense F200型深度传感器参数、柑橘果实尺寸、近景探测范围、数据预处理与特征提取需要完成了深度球截线方法的参数确定。大量室内试验结果表明,深度球截线方法对孤立果实提取的平均成功率为97.8%,贴碰区域内果实提取的平均成功率为76%,而复杂枝环境的果实提取综合成功率为63.8%。该深度球截线的识别方法仅利用有限的深度数据点,在保证原始数据精度的同时降低了运算量和果实特征提取复杂性,能有效应对果叶遮挡问题,实现对贴碰果叶的有效区分,对柑橘果实具有良好的适应性,为采摘机器人在复杂环境下的果实识别与定位提供了新的技术思路。
LIU Jizhan  ZHU Xinxin  YUAN Yan
Jiangsu University,Jiangsu University and Jiangsu University
Key Words:citrus  picking  recognition  depth information  sphere transversal  feature extraction
Abstract:Considering the three-dimensional geometric characteristics of the fruit, leaf and branch objects of citrus are real sphere, slice and thin cylinder, and together with the advantage of depth sensors can collect the depth point cloud of the object. A method to recognize citrus fruits based on depth-sphere transversal was proposed. Firstly, the basic principle and the key parameters of the depth-sphere transversal method for spherical fruits feature extraction were proposed. Secondly, point cloud clustering and regional division method were used to obtain isolated and adhering area, and the feature extraction algorithms of isolated fruits and adhering fruits were put forward to fruit and leaf in isolated areas and fruits or leaves in touching areas, respectively. In addition, in-depth data processing and fruits recognition strategy of a complex environment were obtained. According to the Intel RealSense F200 depth sensor parameters, citrus fruit size, close-range detection range, data preprocessing and the requirements for feature extraction algorithm to determine the parameters of the depth-sphere transversal method were carried out. A large number of indoor tests results indicated that the average success rate was 98.4% by the depth-sphere transversal method in isolated area, and the average success rate was 76% in touching region, while the comprehensive success rate was 63.8% in complex environment. The depth-sphere transversal identification method only used the limited depth data points to ensure the accuracy of the original data and at the same time to reduce the amount of computation and the complexity of fruit feature extraction. This can effectively deal with the problem of fruit and leaf occlusion, and achieve the effective distinction between sticking fruits and leaves. The method had a good adaptability to the citrus fruit, which provided a new idea for robots to recognize and locate fruits in complex environment.

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.

   下载PDF阅读器