摘要
目的:建立一种基于图像处理的番茄重量检测方法以实现无接触式番茄重量检测。方法:通过图像处理得到番茄二值图像,使用像素统计法和最小外接矩形法提取番茄的几何特征与果重真实值进行相关性分析,建立以几何特征为参数的番茄重量检测回归模型。结果:与番茄真实尺寸对比,最小外接矩形法对番茄横、纵径测量误差在3%以内。除果形指数外,其他几何特征与番茄果重呈线性相关,且正面特征与果重的相关关系更显著。建立了3类共20个模型进行预测评估,以番茄正面投影面积与周长、一个侧面图像的投影面积和番茄横径为参数的多元回归模型准确率最高,回归系数为0.962,检测值平均相对误差为0.673%,平均绝对误差为1.425 g。结论:该模型适用于番茄及其他具有类似轴对称形状特征的水果或物品的重量检测。
Objective:A tomato weight detection method based on image processing was established to realize non-contact tomato weight detection.Methods:The binary image of tomato was obtained through image processing.The geometric features of tomato were extracted by pixel statistics and minimum circumscribed rectangle method,and correlation analysis was made between the characteristics and the real value of tomato weight,then the regression model of tomato weight detection with geometric features as parameters was established.Results:Compared with the real size of tomato,the measurement error of transverse and longitudinal diameter of Tomato by minimum external rectangle method was less than 3%.In addition to fruit shape index,other geometric characteristics were linearly correlated with tomato fruit weight,and the correlation between positive characteristics and fruit weight was more significant.Three types of 20 models were established for prediction and evaluation.The multiple regression model with the parameters of tomato front projection area and perimeter,projection area of a side image and tomato transverse diameter had the highest accuracy,the regression coefficient was 0.962,the average relative error of detection value was 0.673%,and the average absolute error was 1.425 g.Conclusion:The model is suitable for the weight detection of tomatoes and other fruits or articles with similar axisymmetric shape characteristics.
作者
何婷婷
李志伟
张馨
张钟莉莉
肖雪朋
董静
HE Ting-ting;LI Zhi-wei;ZHANG Xin;ZHANG Zhong-li-li;XIAO Xue-peng;DONG Jing(Shanxi Agricultural University,Taigu,Shanxi 030801,China;Intelligent Equipment Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;Agricultural Information Software and Hardware Product Quality of the Ministry of Agriculture Key Laboratory of Testing,Beijing 100097,China)
出处
《食品与机械》
北大核心
2022年第10期17-23,共7页
Food and Machinery
基金
北京市科技计划项目(编号:Z201100008020013)
云南重点研发计划项目(编号:202002AE090010)
北京市农科学院创新能力建设项目(编号:KJCX20210402)。
关键词
机器视觉
图像处理
特征提取
番茄重量
machine vision
image processing
feature extraction
tomato weight
