天津农学院学报 ›› 2019, Vol. 26 ›› Issue (2): 74-76.doi: 10.19640/j.cnki.jtau.2019.02.017

• 研究与简报 • 上一篇    下一篇

基于机器视觉技术的血鹦鹉鱼外形评价研究

齐月, 田云臣通信作者   

  1. 天津农学院 计算机与信息工程学院,天津 300384
  • 收稿日期:2019-01-10 出版日期:2019-06-20 发布日期:2019-09-19
  • 通讯作者: 田云臣(1967-),男,教授,硕士,主要从事农业信息技术方面的研究工作。E-mail:tianyunchen@tjau.edu.cn。
  • 作者简介:齐月(1994-),女,硕士在读,主要从事农业信息技术方面的研究工作。E-mail:1564284755@qq.com。
  • 基金资助:
    天津市现代农业产业技术体系创新团队建设专项资金(ITTFRS2017018)

Research on the shape evaluation of red parrot fish based on machine vision technology

QI Yue, TIAN Yun-chen   

  1. College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300384, China
  • Received:2019-01-10 Online:2019-06-20 Published:2019-09-19

摘要: 血鹦鹉鱼的外形是分级的重要因素,分级结果决定其市场价值。目前,血鹦鹉鱼分级主要依靠人工进行,主观性强、效率低。本文介绍了利用机器视觉技术对鹦鹉鱼外形评价的方法,详细阐述了在养殖水体不变的情况下,通过Matlab2017a软件控制摄像头完成图片的采集,并通过二值化、取阈值、去噪声、寻找边界等方法对采集到的图像进行处理的过程,最后介绍了利用metric函数判断鱼体边界所围成的闭合曲线是否趋近于圆形,进而完成血鹦鹉鱼外形评价的方法。试验结果表明,该方法能自动完成血鹦鹉鱼的分级,解决传统方法存在的效率低、误差大等问题。

关键词: 机器视觉, 图像处理, 血鹦鹉鱼, 外形评价

Abstract: The appearance of red parrot fish is an important factor of grading, and the grading results determine its market value. At present, the classification of blood parrot fish mainly relies on artificial, with strong subjectivity and low efficiency. This paper introduced the use of machine vision technology to evaluate the parrot fish appearance by detailed elaboration under the invariable condition of aquaculture water, through Matlab2017a camera image acquisition software control, and through the binarization, threshold, de-noising, finding the boundary, processing the collected image, finally introducing the use of metric function to judge whether the fish boundary of closed curve is tend to be rounded so as to complete blood parrot fish shape evaluation. The experimental results showed that this method can automatically complete the classification of blood parrot fish and solve the problem of low efficiency and large error existing in traditional methods.

Key words: machine vision, image processing, red parrot fish, appearance evaluation

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