Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (4): 1157-1161.DOI: 10.11772/j.issn.1001-9081.2018091895

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Positioning accuracy analysis of optical micropositioning system

CHEN Xiong1, ZOU Xiangjun1, FAN Ke2, LU Jun2   

  1. 1. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education(South China Agricultural University), Guangzhou Guangdong 510642, China;
    2. Guangdong Provincial Key Laboratory of Biocomputing(Guangzhou Institute of Biomedicine and Health, Chinese Academy of Sciences), Guangzhou Guangdong 510530, China
  • Received:2018-09-10 Revised:2018-10-19 Online:2019-04-10 Published:2019-04-10
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (31571568).

光学显微定位系统定位精度分析

陈雄1, 邹湘军1, 樊科2, 卢俊2   

  1. 1. 南方农业机械与装备关键技术教育部重点实验室(华南农业大学), 广州 510642;
    2. 广东省生物医药计算重点实验室(中国科学院广州生物医药与健康研究院), 广州 510530
  • 通讯作者: 邹湘军
  • 作者简介:陈雄(1993-),男,湖北孝感人,硕士研究生,主要研究方向:机器视觉、图像处理;邹湘军(1957-),女,湖南衡阳人,教授,博士生导师,博士,主要研究方向:机器视觉、图像处理、农业机器人;樊科(1985-),男,四川成都人,副研究员,博士,主要研究方向:机器视觉、图像处理、光学工程、自动化。
  • 基金资助:
    国家自然科学基金资助项目(31571568)。

Abstract: In order to improve the accuracy of identification and localization of cell microorganisms by optical micropositioning system, on the one hand, the hand-eye calibration method should be optimized, on the other hand, the accuracy of global image recognition should be improved. Aiming at those, a two-step method for hand-eye calibration of the system was proposed. Firstly, the origin of the system was determined by calibrating the fixed target, and the transformation relationship of the vision module to the origin of the system was obtained. Then, according to the starting point position of each photograph, the number of photoing and the step size of movement, the transformation relationship of the global image to the origin of the system was solved. Finally, in order to further improve the accuracy of the global transformation relationship, an error correction method based on Fourier transform was used to obtain the error of the visual module in movement,then the error was added into the system for compensation. Experimental results show that after error compensation, the micropositioning system has the error mean value in X-axis direction reduced from 10.23 μm to -0.002 μm, the error mean value in Y-axis direction reduced from 6.9 μm to -0.50 μm, and the average positioning accuracy over 99%. The results show that the proposed method can be applied to the optical micropositioning system for high-precision automated capture of cell microorganisms.

Key words: micropositioning system, hand-eye calibration, error correction, Fourier transform

摘要: 为了提高光学显微定位系统对细胞微生物识别定位的精度:一方面,必须改进手眼标定方法;另一方面,需要提高全局图像识别的准确性,因此,提出一种两步法对系统进行手眼标定。首先,通过标定固定靶标来确定系统原点,并得到视觉模块相对于系统原点的转换关系;然后,根据每次拍照的起始点位置、拍照的数量和移动的步长求解出全局图像相对于系统原点的转换关系;最后,为了进一步提高全局转换关系的准确度,提出一种基于傅里叶变换的误差矫正方法,利用傅里叶变换求解出视觉模块在移动过程中的误差,并加入系统进行补偿。实验结果表明,误差补偿之后,系统X轴方向的误差均值从10.23 μm降为-0.002 μm,Y轴方向的误差均值从6.9 μm降为-0.50 μm,显微定位系统的平均定位精度达到了99%以上。结果表明,所提方法可很好地用于光学显微定位系统对细胞微生物进行高精度的自动化抓取。

关键词: 显微定位系统, 手眼标定, 误差矫正, 傅里叶变换

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