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Chinese Agricultural Science Bulletin ›› 2025, Vol. 41 ›› Issue (4): 156-164.doi: 10.11924/j.issn.1000-6850.casb2024-0295

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

LI Shujia1(), SUN Laijun1(), MENG Yahao1, WANG Yichen1, LI Xiaoxu2, FENG Guojun3, YANG Fengyan4   

  1. 1 College of Electronic Engineering, Heilongjiang University, Harbin 150080
    2 Zibo Branch, China Mobile Communications Group Shandong Co., Ltd., Zibo, Shandong 255020
    3 College of Modern Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080
    4 Heilongjiang Agricultural Engineering Vocational College, Harbin 150080
  • Received:2024-05-07 Revised:2024-11-13 Online:2025-01-23 Published:2025-01-23

Abstract:

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 F1 value of the three classification models, it was found that the SVM model outperformed the other two classification models, with a classification accuracy and F1 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.

Key words: common bean, classification, machine vision, image processing, intelligent recognition, machine learning, support vector machine, feature extraction