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

作　　者：丁灿 王文胜 黄小龙[1] DING Can;WANG Wen-sheng;HUANG Xiao-long(School of Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学机电工程学院,北京100192

出　　处：《粮油食品科技》2024年第4期178-184,共7页Science and Technology of Cereals,Oils and Foods

基　　金：国家重点研发计划(2020YFB1713205);北京信息科技大学“青年骨干教师”支持计划(YBT202403)。

摘　　要：花生霉变产生的黄曲霉毒素具有强致癌性,严重影响食品安全。为精准快速的识别霉变花生,提出一种基于机器视觉的霉变花生检测方法。首先对花生图像进行双边滤波降噪,然后将图像转为色调、饱和度、亮度(HSV)空间,通过在色调、饱和度空间内提取的霉变颜色范围叠加亮度空间的开运算处理结果来实现对霉变花生的识别检测。实验结果表明,该方法对于霉变花生的识别精度达到95.3%,处理单帧花生图像耗时为0.6s,通过与其它算法对比,该方法具有快速、准确率高等优点,可以满足霉变花生的实时检测,对花生霉变的分级处理也更加实用。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 

分 类 号：TS227[轻工技术与工程—粮食、油脂及植物蛋白工程] TS214.9[轻工技术与工程—食品科学与工程]