基于计算机视觉的大米裂纹检测研究  

Rice fissure detection using computer vision

作　　者：郑华东[1] 刘木华[1] 吴彦红[1] 黎静[1] 

机构地区：[1]江西农业大学工学院,南昌330045

出　　处：《农业工程学报》2006年第7期129-133,共5页Transactions of the Chinese Society of Agricultural Engineering

基　　金：江西省自然科学基金资助项目(0230019);江西省教育厅科技项目

摘　　要：针对人工目测的传统方法在进行米粒裂纹检验时存在主观性及随意性较大、效率较低、可重复性较差等缺点,在分析大米裂纹光学特征的基础上,在V isua l C++6.0环境下开发了一套大米裂纹计算机识别系统,通过图像二值化、区域标记等方法从原始图像中提取单体米粒图像,并对提取出的单体米粒图像进行灰度拉伸变换处理以突出米粒裂纹特征,然后提取单体米粒的行灰度均值变化曲线,并对曲线进行加权滤波处理,提出了一种基于单体裂纹米粒图像行灰度均值变化特征的大米裂纹检测算法。运用该算法对从金优974、菲优600、冈优182、中优205、89-94等5类大米品种中各选取的6组特殊类样品和5组随机样品进行裂纹检测。试验结果表明,该系统对特殊类大米样品和随机大米样品裂纹率的判断准确率分别为98.37%和97.88%,为进一步完善大米品质的计算机视觉检测提供了理论和实践基础。Rice fissure detection using traditional manual method encounters with some problems such as great subjectivity, high random, low efficiency and bad repeatability. A rice fissure detection system was developed after researching the illumination characteristic of fissured rice in the platform of VC＋＋6.0 software. Single rice images were picked up from originally obtained mass image with methods of binary treatment, region marking. Rice fissure characteristics was emphasized by gray transformation, then the curve of row-mean gray value of single rice kernel image was drawn and a filter algorithm was designed to smoothen the curve. Subsequently, an algorithm was designed to detect rice fissure based on row-mean gray value of single rice kernel image. Finally, a detecting experiment was carried out with six groups of specially-selected samples and five randomly-selected samples of five varieties of rice kernels such as Jinyou974, Feiyou600, Gangyou182, Zhongyou205, 89-94. The results show that the detecting accuracy of the system for specially-selected samples and randomly-selected samples were 98.37 per cent and 97.88 per cent, respectively. It could help to improve rice quality detection with computer vision theoretically and practically.

关 键 词：大米 计算机视觉 图像处理 裂纹检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TS212.7[自动化与计算机技术—计算机科学与技术]