A research of the external quality grading detection for northeastern pine nuts based on improved C- V model
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摘要: 提出了东北松子外部品质的无损等级划分方法。利用CCD相机获取松子图像,采用改进的C-V模型实现松子轮廓特征的提取;利用数学形态学的方法,提取松子的果长、横径特征参数,并与实际测量值间构建数学模型;根据提取出的特征参数,建立松子外部品质综合等级评定标准。实验结果表明,采用本文方法能够实现同时对多个东北松子外部品质的等级划分,且划分的平均准确率为97.2%。Abstract: A nondestructive gradation method has been introduced for the external quality of northeastern pine nuts in this paper.Images of pine nuts were got by a CCD camera with improved C-V model to extract contour features.Feature parameters of pine nuts ' length and width were extracted by the method of mathematical morphology,and according to those and the measured values the mathematical model was established,and a comprehensive evaluation standard for the external quality of pine nuts grade was established too.The results were demonstrated that the external quality of multiple northeastern pine nuts could be graded simultaneously by the method in this paper with the accuracy of 97.2%.
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[1] 陈宝,南江,王星,等.松子的开发与利用[J].现代农业科学,2010,1(20):160. [2] 张道东.基于机器视觉技术的蜜桔、脐橙外部品质在线检测分级研究[D].杭州:浙江大学,2011. [3] Sergio C,Nuria A,Enrique M,et al.Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables[J].Food and Bioprocess Technology,2011,4(5):487-504.
[4] Devrim U,Bernard G,Olivier K,et al.Automatic grading of Bi-colored apples by multispectral machine vision[J].Computers and Electronics in Agriculture,2011,75(1):204-212.
[5] Muhammad M,Peeyush S.Detecting rottenness caused by Penicillium genus fungi in citrus fruits using machine learning techniques[J].Computers and Electronics in Agriculture,2012,39(1):780-785.
[6] 饶秀勤,应义斌.水果按表面颜色分级的方法[J].浙江大学学报(工学版),2009,43(5):869-871. [7] Yudong Z,Lenan W.Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine[J].Sensors,2012,12(9):12489-12505.
[8] Krishna K P.A.Kar S N,Jha M A.Machine vision system:a tool for quality inspection of food and agricultural products[J].Food Science and Technology,2012,49(2):123-141.
[9] Lorente D,Aleixos N,Gomez-Sanchis J,et al.Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment[J].Food and Bioprocess Technology,2012,5(4):1121-1142.
[10] 刘建军,姚立健,彭樟林.基于机器视觉的山核桃等级检测技术[J].浙江农业学报,2010,22(6):854-858. [11] 葛亮,陈红,任金海,等.机器视觉在香菇品质分级中的应用[J].中国食用菌,2011,30(1):8-9. [12] 山海涛,郝向阳,马淑宇,等.影像畸变对基本矩阵估计精度的影响分析[J].测绘科学技术学报,2010,27(1):50-53. [13] 马广彬,章文毅,陈甫.图像几何畸变精校正研究[J].计算机工程与应用,2007,43(9):45-48. [14] Zhang Z Y.A flexible new technique for camera calibration[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(11):1330-1334.
[15] 王大凯,侯榆青,彭进业.图像处理的偏微分方程方法[M].北京:科学出版社,2008:103-105. [16] Chan T,Vese L.Active contour without edges[J].IEEE Image Processing,2001,10(2):266-277.
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