基于机器视觉的鸡蛋品质无损检测方法
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摘要
目的以蛋品质量评价指标—哈夫单位值为检测标准,建立一种基于机器视觉的鸡蛋品质无损检测方法。方法通过摄像头捕捉到鸡蛋图像信息,利用MATLAB对鸡蛋图像的G分量以及I分量进行特征参数提取,并计算出与鸡蛋新鲜度相关的4个特征参数:蛋黄面积比、气室面积比、气室高度比与气室直径比,将其作为自变量,通过高精度游标卡尺实测每个鸡蛋样本哈夫值作为因变量,分别建立一元回归模型,寻找特征参数与哈夫值的关系,并根据哈夫值对鸡蛋新鲜度进行分级。结果实验表明,所测4个特征参数中,蛋黄面积比与哈夫值存在较强的相关性,相关系数为0.78,拟合优度为0.62,蛋黄面积比越小,鸡蛋哈夫值越大,说明鸡蛋越新鲜。结论基于机器视觉的鸡蛋品质无损检测方法不仅具有较强的应用价值,还可以为鸡蛋品质智能分级提供技术支撑。
Objective To establish a nondestructive testing method for egg quality based on machine vision wased, with the evaluation index of egg quality-Haff unit value as test standard. Methods Images of eggs were captured by a camera, than characteristic parameters in I component images and G component images of eggs were extracted based on MATLAB. Four characteristic parameters of egg freshness could be calculated, including tatio of egg yolk area, air chamber area, chamber height and chamber diameter. The single-element regression model was established with Haff values measured by high precision vernier caliper as dependent variables and the 4 characteristic parameters as independent variables to find the relationship between them respectively, and then the egg freshness was graded according to Haff values. Results The experiment showed that there was a strong correlation between the area ratio of egg yolk and Haff value. The correlation coefficient was 0.78 and the goodness of fit was 0.62. The smaller the egg yolk area ratio, the larger the egg Huff value, indicating that the egg was fresher. Conclusion The non-destructive testing method for egg quality not only has a strong application value, but also provides technical support for egg quality intelligent grading.
Objective To establish a nondestructive testing method for egg quality based on machine vision wased, with the evaluation index of egg quality-Haff unit value as test standard. Methods Images of eggs were captured by a camera, than characteristic parameters in I component images and G component images of eggs were extracted based on MATLAB. Four characteristic parameters of egg freshness could be calculated, including tatio of egg yolk area, air chamber area, chamber height and chamber diameter. The single-element regression model was established with Haff values measured by high precision vernier caliper as dependent variables and the 4 characteristic parameters as independent variables to find the relationship between them respectively, and then the egg freshness was graded according to Haff values. Results The experiment showed that there was a strong correlation between the area ratio of egg yolk and Haff value. The correlation coefficient was 0.78 and the goodness of fit was 0.62. The smaller the egg yolk area ratio, the larger the egg Huff value, indicating that the egg was fresher. Conclusion The non-destructive testing method for egg quality not only has a strong application value, but also provides technical support for egg quality intelligent grading.
引文
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[15]陈明晶,方源敏,陈杰.最小二乘法和迭代法圆曲线拟合[J].测绘科学,2016,41(1):194-197.Chen MJ,Fang YM,Chen J.Fitting of circular curve based on least square method and iterative method[J].Sci Surv Mapp,2016,41(1):194-197.
[2]潘爱銮,孙静,吴艳,等.江汉鸡蛋品质测定与分析[J].湖北农业科学,2017,56(16):3113-3116.Pan AL,Sun J,Wu Y,et al.Study on egg quality of Haniiang chicken[J].Hubei Agric Sci,2017,56(16):3113-3116.
[3]董传豪,徐亚欧,郑玉才,等.3品种鸡蛋外在品质及营养价值的对比分析[J].江苏农业科学,2016,44(10):351-354.Dong CH,Xu YO,Zhen YC,et al.Comparative analysis of external quality and nutritional value of 3 varieties of eggs[J].jiangsu Agric Sci,2016,44(10):351-354.
[4]王巧华,王彩云,马美湖.基于机器视觉的鸭蛋新鲜度检测[J].中国食品学报,2017,17(8):268-274.Wang QH,Wang CY,Ma MH.Duck egg freshness detection based on machine vision[J].J Chin Inst Food Sci Technol,2017,17(8):268-274.
[5]宋爱祎.鸡蛋品质的测定及氨基酸螯合钙的工艺研究[D].乌鲁木齐:新疆农业大学,2012.Song AW.Determination of egg quality and research of amino acids chelating calcium[D].Urumqi:Xinjiang Agricultural University,2012.
[6]刘燕德,乔振先.鸡蛋光特性及其与析鲜度的相关性研究[J].江西农业大学学报,2002,24(1):45-47.Liu YD,Qiao ZX.A correlative study on the opitical properties and freshness of chicken-egg[J].Acta Agric Univ Jiangxiensis,2002,24(1):45-47.
[7]印爱丽.基于图像处理的光纤缠绕均匀度评价方法的研究[D].南京:南京理工大学,2012.Yin AL.Research on method of fiber winding uniformity evaluation based on image processing[D].Nanjing:Nanjing University of Science and Technology,2012.
[8]颜秉忠.机器视觉技术在玉米苗期杂草识别中的应用[J].农机化研究,2018,40(3):212-216.Yan BZ.Identification of weeds in maize seedling stage by machine vision technology[J].J Agric Mech Res,2018,40(3):212-216.
[9]姜沛宏,张玉华,钱乃余,等.基于机器视觉技术的肉新鲜度分级方法研究[J].食品科技,2015,(3):296-300.Jiang PH,Zhang YH,Qian NY,et al.Research on method to freshness grading of meat based on machine vision technology[J].Food Sci Technol,2015,(3):296-300.
[10]刘亚丽.机器视觉技术在农业工程中的应用[J].电脑知识与技术,2017,13(23):149-151.Liu YL.Application of machine vision technology in agricultural engineering[J].Comput Knowl Technol,2017,13(23):149-151.
[11]白修云,刘旭明,龚海岩,等.我国与欧美鲜禽蛋质量分级及检验标准比较解析[J].中国家禽,2014,36(1):51-53.Bai XY,Liu XM,Gong HY,et al.Comparison of quality grading and inspection standards for fresh eggs in China and Europe and America[J].China Poult,2014,36(1):51-53.
[12]陈微微.基于颜色特征提取的图像搜索引擎研究[D].重庆:重庆理工大学,2012.Chen WW.Research on image search engine based on color feature extraction[D].Chongqing:Chongqing University of Technology,2012.
[13]沈昊.基于DSP图像处理的鸡蛋新鲜度实时无损检测研究[D].武汉:华中农业大学,2010.Shen H.Real time nondestructive detection of egg freshness based on DSPimage processing[D].Wuhan:Huazhong Agricultural University,2010.
[14]魏小彪,王树才.鸡蛋新鲜度综合无损检测模型及试验[J].农业工程学报,2009,25(3):242-247.Wei XB,Wang SC.Comprehensive nondestructive testing model and experiment of egg freshness[J].Trans Chin Soc Agric Eng,2009,25(3):242-247.
[15]陈明晶,方源敏,陈杰.最小二乘法和迭代法圆曲线拟合[J].测绘科学,2016,41(1):194-197.Chen MJ,Fang YM,Chen J.Fitting of circular curve based on least square method and iterative method[J].Sci Surv Mapp,2016,41(1):194-197.