粮油食品科技2024，Vol.32Issue(4)：178-184,7.DOI:10.16210/j.cnki.1007-7561.2024.04.022
基于改进HSV空间的机器视觉花生霉变检测方法
Machine Vision Detection Method for Peanut Mold Based on Improved HSV Space
摘要
Abstract
The aflatoxin produced by peanut mildew is highly carcinogenic,and it seriously affects food safety.In order to accurately and quickly identify moldy peanuts,this project proposes a detection method for moldy peanuts based on machine vision.Firstly,the peanut image was double-sided filtering and noise reduction,and then the image was converted to HSV space.The moldy peanut was recognized and detected by superimposing the mold color range extracted in H and S space and the open processing results of V space.The experimental results showed that the recognition accuracy of this method for moldy peanuts reached 95.3%,and the processing time for a single frame of peanut image was 0.6 seconds.Compared with other algorithms,this method had the advantages of fast speed and high accuracy,which can meet the real-time detection of moldy peanuts.At the same time,the grading processing of peanut mold is also more practical.关键词
霉变花生/机器视觉/HSV色彩空间/图像处理/双边滤波Key words
moldy peanuts/machine vision/HSV color space/image processing/bilateral filtering分类
轻工纺织引用本文复制引用
丁灿,王文胜,黄小龙..基于改进HSV空间的机器视觉花生霉变检测方法[J].粮油食品科技,2024,32(4):178-184,7.基金项目
国家重点研发计划(2020YFB1713205) （2020YFB1713205）
北京信息科技大学"青年骨干教师"支持计划(YBT202403) National Key Research and Development Project of China(No.2020YFB1713205) （YBT202403）
Young Backbone Teacher Support Plan of Beijing Information Science and Technology University(No.YBT202403) （No.YBT202403）
