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基于计算机视觉的食品中大肠杆菌快速定量检测 被引量:10

Rapid method for enumeration of Escherichia coli in food based on computer vision
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摘要 利用大肠杆菌能发酵乳糖产酸从而使伊红美兰混合液产生沉淀、溶液变色的特性,设计了一套基于颜色特征识别技术的食品中大肠杆菌快速定量检测系统,通过16 h培养后溶液颜色的变化程度来判断待测液中大肠杆菌的数目。系统自动提取发酵后溶液图像的H、I、S颜色分量作为输入向量,自动调用训练好的BP神经网络模型得到大肠杆菌数。试验结果表明:该方法的检测结果与传统方法的相关性好,检测时间在18 h以内,远少于传统方法的6天,有效提高了产品的销售品质。 The speciality that the Escherichia coli can ferment lactose to produce acid which can produce depositions and make the indicator's color changed was utilized,an automatic detection system for enumeration of Escherichia coli in food based on color feature recognition technology was designed and the color change degree after incubating for 16 h was used to judge the Escherichia coli counts in the detection samples.The system can automatically extract the H、I、S color vector to act as the input vector and transfer the trained BP neural network to get the Escherichia coli counts.The experiments indicate that comparisons of counts of Escherichia coli by the rapid automatic detection system and by the traditional method closed correlated.Moreover,by using this rapid detection system,the Escherichia coli in food accurately enumerate within 18 h,which is much shorter than the 6 days detection time by the traditional method,which will greatly improve the products sale quality.
作者 殷涌光 丁筠
出处 《吉林大学学报(工学版)》 EI CAS CSCD 北大核心 2009年第S2期344-348,共5页 Journal of Jilin University:Engineering and Technology Edition
基金 国家科技支撑计划项目(2007BAD55B06) 吉林省科技发展计划项目(20060216)
关键词 食品机械 计算机视觉 大肠杆菌快速检测 人工神经网络 颜色特征识别 food machinery machine vision escherichia coli rapid detection artificial neural network color feature recognition
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参考文献6

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