基于机器视觉的小粒咖啡豆的检测技术
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云南省科技计划项目(2018ZF004);云南省高校工程研究中心建设计划项目(云教科[2016]37号)


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    摘要:

    设计搭建了基于机器视觉的小粒咖啡豆检测分级系统,系统由进料部、匀料筛分部、色选部、气动部、收料部以及电控箱组成。开发了基于OpenCV和visual studio的系统分析与控制软件,实现咖啡豆果径宽度和烘焙程度的检测分级。基于Blob分析方法对小粒咖啡生豆进行图像分割,利用最小外接矩形方法对果径宽度进行特征提取,采用HSV颜色空间模型提取小粒咖啡豆的颜色特征值,最终将小粒咖啡生豆分为5个等级,将烘焙程度分为浅度、中度、深度3个程度。系统运行验证试验结果表明,对小粒咖啡生豆的果径宽度检测的平均误差为1.275%,烘焙程度检测的准确率为88.9%。

    Abstract:

    The detection and grading system of small grain coffee bean was designed based on the machine vision. The system consisted of the feeding part, the sizing part, the color selection part, the pneumatic part, the receiving part and the electric control box. The system analysis and control software based on OpenCV and visual studio was developed to realize the detection and classification of coffee bean diameter and baking degree. Based on Blob analysis method, the image was extracted by using the minimum circumscribed rectangle method. The color feature value of small coffee beans was extracted by HSV color space model. The degree of baking is identified. Finally, the small–grain coffee green beans are divided into five grades and the degree of baking is divided into three levels: shallow, medium, and deep. The verification test results of the system showed that the average error of the detection of the diameter of the small bean coffee beans was 1.275% and the accuracy of the baking degree detection was 88.9%.

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赵晶,张付杰,冯帅辉,杨薇,王璐,李梦丽.基于机器视觉的小粒咖啡豆的检测技术[J].湖南农业大学学报:自然科学版,2018,44(6):.

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  • 在线发布日期: 2018-12-25
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