首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于计算机视觉的花生霉变程度检测
引用本文:王金英,董礼.基于计算机视觉的花生霉变程度检测[J].农机化研究,2019(8):223-226.
作者姓名:王金英  董礼
作者单位:秦皇岛职业技术学院
基金项目:河北省科技厅课题(18457660D)
摘    要:花生是重要的油料作物,且富含蛋白质和维生素,具有很高的食用价值。黄曲霉和寄生曲霉能引起花生的霉变,产生强致癌物质黄曲霉素,对人类健康产生严重的威胁。通过对霉变程度的检测,可以为霉变花生的清选提供条件,极大地提高花生食用的安全性。为此,基于计算机视觉技术,用相机拍摄花生的图像,采用维纳滤波处理去除噪音,用B分量进行图像分割后获得目标区域图像。选用H颜色分量作为反映花生霉变程度的特征参数,根据设定的阈值评判霉变等级。该方法对花生霉变程度检测的准确率超过93%,处理单张图像耗时1 s,可以满足实时检测的要求,为花生的在线分选提供了技术支撑。

关 键 词:花生  霉变  计算机视觉  检测

Computer Vision-based Detection of Mildew in Peanut
Wang Jinying,Dong Li.Computer Vision-based Detection of Mildew in Peanut[J].Journal of Agricultural Mechanization Research,2019(8):223-226.
Authors:Wang Jinying  Dong Li
Institution:(Qinhuangdao Vocational and Technical College,Qinhuangdao 066100,China)
Abstract:Peanuts are important oil crops.They are also rich in protein and vitamins and have a high food value.Aspergillus flavus and Aspergillus parasiticus can cause mildew in peanuts,producing a strong carcinogen aflatoxin,which poses a serious threat to human health.Through the detection of moldiness,it can provide conditions for the selection of moldy peanuts and greatly improve the safety of peanuts.This paper is based on computer vision technology,using a camera to take pictures of peanuts,using Wiener filtering to remove noise,and using B-components for image segmentation to obtain images of the target area.The H color component was selected as a characteristic parameter reflecting the degree of mildew in peanut,and the mildew grade was judged according to the set threshold value.The accuracy of the method for the detection of mildew degree of peanut exceeds 93%,and it takes 1s to process the single-sheet image,which can meet the requirements of real-time detection and provide technical support for on-line sorting of peanuts.
Keywords:peanut  mildew  computer vision  detection
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号