一种新型的大白菜种子自动分拣系统。

A Novel Auto-Sorting System for Chinese Cabbage Seeds.

机构信息

Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Tai-Chung 402, Taiwan.

出版信息

Sensors (Basel). 2017 Apr 18;17(4):886. doi: 10.3390/s17040886.

DOI:10.3390/s17040886

PMID:28420197

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5424763/

Abstract

This paper presents a novel machine vision-based auto-sorting system for Chinese cabbage seeds. The system comprises an inlet-outlet mechanism, machine vision hardware and software, and control system for sorting seed quality. The proposed method can estimate the shape, color, and textural features of seeds that are provided as input neurons of neural networks in order to classify seeds as "good" and "not good" (NG). The results show the accuracies of classification to be 91.53% and 88.95% for good and NG seeds, respectively. The experimental results indicate that Chinese cabbage seeds can be sorted efficiently using the developed system.

摘要

本论文提出了一种基于机器视觉的新型大白菜种子自动分拣系统。该系统包括进出口机构、机器视觉硬件和软件以及分拣种子质量的控制系统。所提出的方法可以估计种子的形状、颜色和纹理特征，这些特征作为神经网络的输入神经元，以便将种子分类为“好”和“不好”（NG）。结果表明，对于好种子和 NG 种子，分类的准确率分别为 91.53%和 88.95%。实验结果表明，所开发的系统可以有效地对大白菜种子进行分拣。