基于机器视觉的菜豆种子品种智能识别与分类  

Intelligent Identification and Classification of Common Bean Seed Varieties Based on Machine Vision

作　　者：李淑佳 孙来军[1] 蒙亚浩 王祎辰 李晓旭 冯国军[3] 杨凤艳 LI Shujia;SUN Laijun;MENG Yahao;WANG Yichen;LI Xiaoxu;FENG Guojun;YANG Fengyan(College of Electronic Engineering,Heilongjiang University,Harbin 150080;Zibo Branch,China Mobile Communications Group Shandong Co.,Ltd.,Zibo,Shandong 255020;College of Modern Agriculture and Ecological Environment,Heilongjiang University,Harbin 150080;Heilongjiang Agricultural Engineering Vocational College,Harbin 150080)

机构地区：[1]黑龙江大学电子工程学院,哈尔滨150080 [2]中国移动通信集团山东有限公司淄博分公司,山东淄博255020 [3]黑龙江大学现代农业与生态环境学院,哈尔滨150080 [4]黑龙江农业工程职业学院,哈尔滨150080

出　　处：《中国农学通报》2025年第4期156-164,共9页Chinese Agricultural Science Bulletin

基　　金：黑龙江省自然科学基金项目“基于多源信息融合与SVM的水稻品质分类与年份迭代优化研究”(SS2021C005);黑龙江省重点研发计划项目“高端电子系统板级和设备级的多余物高精密检测技术研发”(2022ZX03A06)。

摘　　要：为基于机器视觉(MV)设计一种低成本、高效且无损的菜豆种子识别、分类的方法,采集6个品种2751粒菜豆种子的图像信息,在对图像进行二值化、颜色提取、形态学操作等图像处理的基础上,提取包括颜色特征、纹理特征以及几何特征在内的9种特征作为分类的依据,分别建立K近邻(KNN)、随机森林(RF)、支持向量机(SVM)3种分类模型,对菜豆种子的品种进行分类。对比3种分类模型的混淆矩阵、准确率及F_(1)值后发现,SVM模型的分类效果上最优,其分类准确率和F_(1)值分别达到97.7%、0.977。研究表明,利用MV可以实现对菜豆种子的精准识别和分类。The aim of this study was to design a low-cost,efficient and non-destructive method for identifying and classifying common bean seeds based on machine vision(MV).In this study,image information of 2751 seeds of six varieties of common beans was collected,and based on image processing such as binarization,color extraction and morphological operations,nine features including color features,texture features and geometric features were extracted as the basis of classification,and K-nearest neighbor(KNN),random forest(RF),and support vector machine(SVM)classification models were established to classify the varieties of bean seeds.After comparing the confusion matrix,accuracy and F_(1) value of the three classification models,it was found that the SVM model outperformed the other two classification models,with a classification accuracy and F_(1) value of 97.7%and 0.977,respectively.The results of the study show that accurate identification and classification of common bean seeds can be achieved using MV.

关 键 词：菜豆 分类 机器视觉 图像处理 智能识别 机器学习 支持向量机 特征提取 

分 类 号：S529[农业科学—作物学] TP391.41[自动化与计算机技术—计算机应用技术] TP181[自动化与计算机技术—计算机科学与技术]