江汉大学学报(自然科学版) ›› 2021, Vol. 49 ›› Issue (3): 64-69.doi: 10.16389/j.cnki.cn42-1737/n.2021.03.009

• 计算机科学 • 上一篇    下一篇

基于机器视觉的蓝莓果实分级研究

李建航,易克传*,刘浪,张新伟,孙业荣   

  1. 安徽科技学院 机械工程学院,安徽 凤阳 233100
  • 发布日期:2021-05-18
  • 通讯作者: 易克传
  • 作者简介:李建航(1993— ),男,硕士生,研究方向:农业智能制造及装备技术。
  • 基金资助:
    安徽省教育厅重点项目(KJ2020A0068)

Research on Blueberry Fruit Grading Based on Machine Vision

LI Jianhang,YI Kechuan*,LIU Lang,ZHANG Xinwei,SUN Yerong   

  1. College of Mechanical Engineering,Anhui Science and Technology University,Fengyang 233100,Anhui,China
  • Published:2021-05-18
  • Contact: YI Kechuan

摘要: 针对蓝莓果实的传统分拣方法效率低的问题,提出利用机器视觉技术进行蓝莓果实投影面积的数字化识别与计算。采用最大类间方差法对蓝莓果实图像进行分割,并用形态学处理方法去除连通区域,采用最小二乘法对蓝莓果实区域进行近似圆拟合,经过标定后计算出蓝莓果实的面积和周长。结果显示,以手动分割结果作为标准计算相对准确率情况下,采用蓝莓果实面积作为分级标准比周长作为分级标准更加精确,效果更好。经过图像处理后计算出面积的平均准确率达到98. 93%,效 果稳定,具有较高的准确度,为蓝莓果实的自动分级提供了重要依据。

关键词: 机器视觉, 蓝莓果实, 最小二乘法拟合, 图像处理

Abstract: In view of the low efficiency of the traditional sorting method of blueberry fruit,the digital recognition and calculation of the projection area of blueberry fruit were proposed by using machine vision technology. The image of blueberry fruit was divided by the maximum inter-class variance method,the connected domain area was removed by morphological processing method,the blueberry area was approximately rounded by the least-square method,and the area and perimeter of blueberry fruit were calculated after calibration. The results showed that in the case of manual segmentation results as the standard for calculating relative accuracy,the use of the blueberry area as the grading standard was more accurate than the use of perimeter as the grading standard,and the effect was better. After the image processing,the average accuracy of the calculated area reached 98. 93%,the effect was stable,with high accuracy. It provides an important basis for the automatic grading of blueberry fruit.

Key words: machine vision, blueberry fruit, least-squares fitting, image processing

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