草莓重量和形状图像特征提取与在线分级方法
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摘要
针对草莓在采后分级生产中存在分级规格不一和效率低下等问题,提出一种基于机器视觉技术的草莓重量与形状分级方法。利用阈值分割法检测草莓果实,提取果实周长和面积参数,通过多元线性回归分析建立草莓重量分级模型;提取果实的低频椭圆傅里叶系数作为形状特征参数,并对支持向量机进行训练,建立草莓形状分级模型。选用200个草莓样本进行试验,结果表明:重量分级正确率为89.5%,形状分级正确率为96.7%,平均运算时间分别为64ms和39ms。试验验证了该方法的鲁棒性和实时性。
To deal with the classification problems of strawberry in production,a machine vision based strawberry weight and shape grading method was proposed.The strawberry image was segmented by thresholding to extract the fruit.The area and perimeter parameters of the fruit were then calculated and used to build the strawberry weight grading model through regression analysis.Elliptic Fourier descriptor was used to extract the shape features of the fruit,and these shape features were applied to train a support vector machine(SVM) which represented the strawberry shape grading model.200 samples of strawberries were selected to test both models,and the results showed that the weight grading accuracy was 89.5%,the shape grading accuracy was 96.7%,and the average calculation time were 64 ms and 39 ms,respectively.Therefore,the approaches for grading strawberries were robust and effective.
To deal with the classification problems of strawberry in production,a machine vision based strawberry weight and shape grading method was proposed.The strawberry image was segmented by thresholding to extract the fruit.The area and perimeter parameters of the fruit were then calculated and used to build the strawberry weight grading model through regression analysis.Elliptic Fourier descriptor was used to extract the shape features of the fruit,and these shape features were applied to train a support vector machine(SVM) which represented the strawberry shape grading model.200 samples of strawberries were selected to test both models,and the results showed that the weight grading accuracy was 89.5%,the shape grading accuracy was 96.7%,and the average calculation time were 64 ms and 39 ms,respectively.Therefore,the approaches for grading strawberries were robust and effective.
引文
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[25]邹小波,赵杰文.基于小波去噪和支持向量机的苹果品种识别法[J].仪器仪表学报,2007,28(3):534-538.Zou Xiaobo,Zhao Jiewen.Distinguishing cultivar apples by electronic nose based on multiresolution decomposition and support vector machine[J].Chinese Journal of Scientific Instrument,2007,28(3):534-538.
[26]Pozo-Ba?os M D,Ticay-Rivas J R,Alonso J B,et al.Features extraction techniques for pollen grain classification[J].Neurocomputing(S0925-2312),2015,150:377.
[2]周雪青,张晓文,邹岚,等.水果自动检测分级设备的研究现状和展望[J].农业技术与装备,2013(2):9-11.
[3]孔彦龙,高晓阳,李红玲,等.基于机器视觉的马铃薯质量和形状分选方法[J].农业工程学报,2012,28(17):143-148.Kong Yanlong,Gao Xiaoyang,Li Hongling,et al.Potato grading method of mass and shapes based on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(17):143-148.
[4]王伟,郑永果,卫文学.基于机器视觉的在线电池检测系统研究[J].系统仿真学报,2006,18(增1):425-426,429.Wang Wei,Zheng Yongguo,Wei Wenxue.Research on Application of Online Battery Checkup Based on Machine Vision[J].Journal of System Simulation,2006,18(S1):425-426,429.
[5]刘良江,王耀南.基于机器视觉的滚动轴承外径检测系统[J].系统仿真学报,2007,19(21):4981-4984,4989.Liu Liangjiang,Wang Yaonan.Rolling Bearing Outside Diameter Inspection System Based on Machine Vision[J].Journal of System Simulation,2007,19(21):4981-4984,4989.
[6]王昭,张平.机器视觉辅助的UAV半自主着陆系统[J].系统仿真学报,2010,22(增1):66-69.Wang Zhao,Zhang Ping.Vision-Aided SemiAutonomous Landing System for UAV[J].Journal of System Simulation,2010,22(S1):66-69.
[7]戴天虹,王克奇,杨少春.基于颜色特征对木质板材分级的研究[J].系统仿真学报,2008,20(5):1372-1376.Dai Tianhong,Wang Keqi,Yang Shaochun.Research on Wooden Board Classification Based on Color and Texture Features[J].Journal of System Simulation,2008,20(5):1372-1376.
[8]姬张建,袁运斌,柴艳菊,等.改进的DGPS/INS/视觉组合导航算法研究[J].系统仿真学报,2011,23(12):2738-2743,2749.Ji Zhangjian,Yuan Yunbin,Chai Yanju,et al.Research on Improved DGPS/INS/Vision Integrated Navigation Technique[J].Journal of System Simulation,2011,23(12):2738-2743,2749.
[9]周维,许海霞.一种摄像机姿态估计方法[J].系统仿真学报,2011,23(12):2582-2587.Zhou Wei,Xu Haixia.Method for Camera Pose Estimation[J].Journal of System Simulation,2011,23(12):2582-2587.
[10]永田雅輝,木下統,浅野克典,等.イチゴの自動選別システムに関する研究(第1報)画像処理による選別のための果形判別法[J].農業機械学会誌,1996,58(5):57-63.
[11]曹其新,吕恬生,永田雅辉.草莓拣选机器人的开发[J].上海交通大学学报,1999,33(7):880-884.Cao Qixin,LüTiansheng,Masateru Nagata.Development of the strawberry sorting robot[J].Journal of Shanghai Jiao Tong University,1999,33(7):880-884.
[12]Xu LiMing,Zhao Yanchao.Automated strawberry grading system based on image processing[J].Computer&Electronics in Agriculture(S0168-1699),2010,71(8):32-39.
[13]Elmsry G M,Elsheikh I H,Morsh N E.Colour grading of strawberry using computer vision and backpropagation artifical neural network[J].Mansoura University Journal of Agricultural Sciences(S2090-3685),2009,34(6):7063-7077.
[14]苟爽,张宁,张云伟,等.基于计算机视觉的草莓等级判别研究[J].安徽农业科学,2015,43(21):370-373.Gou Shuang,Zhang Ning,Zhang Yunwei,et al.Research on grade discrimination of strawberry based on computer vision[J].Journal of Anhui Agri.Sci.,2015,43(21):370-373.
[15]陈科尹,邹湘军,熊俊涛,等.基于视觉显著性改进的水果图像模糊聚类分割算法[J].农业工程学报,2013,29(6):157-165.Chen Keyin,Zou Xiangjun,Xiong Juntao,et al.Improved fruit fuzzy clustering image segmentation algorithm based on visual saliency[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(6):157-165.
[16]Graham R L,Graham R L.An Efficient Algorithm for Determining the Convex Hull of a Finite Planar Set[J].Inf.proc.Lett(S0020-0190),1972(72):132-133.
[17]Agarwal P,Arkin E,Clark K,et al.Computational geometry in C[M].Cambridge University Press,1998.
[18]Mebatsion H K,Paliwal J,Jayas D S.Evaluation of variations in the shape of grain types using principal components analysis of the elliptic Fourier descriptors[J].Computers&Electronics in Agriculture(S0168-1699),2012,80(80):63-70.
[19]张嘉桐,李雪妍,郭树旭,等.基于椭圆傅里叶描述子的形状表示的研究[J].计算机工程与应用,2014,50(2):170-174.Zhang Jiatong,Li Xueyan,Guo Shuxu,et al.Study on shape representation based on elliptic fourier descriptor[J].Computer Engineering and Applications,2014,50(2):170-174.
[20]Sokic E,Konjicija S.Shape description using phase-preserving Fourier descriptor[C]//Multimedia and Expo(ICME),2015 IEEE International Conference on.IEEE,2015:1-6.
[21]Nixon M S,Aguado A S.Feature extraction and image processing[M].Newnes,2002:349-378.
[22]李航.统计学习方法[M].北京:清华大学出版社,2012:95-135.Li Hang.Statistical Learning Method[M].Beijing:Tsinghua University Press,2012:95-135.
[23]Hsu C W,Chang C C,Lin C J.A Practical Guide to Support Vector Classification[D].Taipei,Taiwan:National Taiwan University,2003.
[24]中华人民共和国农业部.NY/T 1789-2009草莓等级规格[S].2009.Ministry of Agriculture of the People's Republic of China.NY/T 1789-2009 Strawberry Grade Specification[S].2009.
[25]邹小波,赵杰文.基于小波去噪和支持向量机的苹果品种识别法[J].仪器仪表学报,2007,28(3):534-538.Zou Xiaobo,Zhao Jiewen.Distinguishing cultivar apples by electronic nose based on multiresolution decomposition and support vector machine[J].Chinese Journal of Scientific Instrument,2007,28(3):534-538.
[26]Pozo-Ba?os M D,Ticay-Rivas J R,Alonso J B,et al.Features extraction techniques for pollen grain classification[J].Neurocomputing(S0925-2312),2015,150:377.