吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (6): 1811-1817.doi: 10.13229/j.cnki.jdxbgxb201406042

Previous Articles     Next Articles

Online sorting of irregular potatoes based on I-RELIEF and SVM method

ZHANG Bao-hua1, 2, HUANG Wen-qian2, LI Jiang-bo2, ZHAO Chun-jiang1, 2, LIU Cheng-liang1, HUANG Dan-feng1   

  1. 1.State Key Laboratory of Mechanical System and Vibration, Shanghai Jiaotong University, Shanghai 200240, China;
    2.Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
  • Received:2013-04-26 Online:2014-11-01 Published:2014-11-01

RICH HTML

0   

PDF (PC)

442

Abstract: An online sorting method of irregular potatoes is proposed. First, the R-component image is extract, and then the binary image and boundary image are obtained by thresholding method. Second, thirteen essential geometrical features, such as eccentricity, rectangle degree and roundness, and ten Fourier descriptors are extracted. Third, the geometrical features of the potato image sample are feed into the module of I-RELIEF algorithm, which exports a weight for each feature. Fourth, the features of the potato image sample with weights are feed into the training module of Support Vector Machine (SVM). Finally, the classifier model is used to make decision and achieve the grading result online based on the potato's features and weights. Results show that the SVM method can detect and sort four potatoes per second with the help of I-RELIEF module, and the overall accuracy is 98.1%.

Key words: computer vision, potato sorting, fourier descriptor, in-line detection, support vector machine(SVM)

CLC Number: 

  • S126
[1] Moreda G P, Muñoz M A, Ruiz-Altisent M, et al. Shape determination of horticultural produce using two-dimensional computer vision—a review[J]. Journal of Food Engineering, 2012, 108(2):245-261.
[2] Zhang B H, Huang W Q, Li J B, et al. Principles, development and applications of computer vision for external quality inspection of fruits and vegetables: A review[J]. Food Research International, 2014, 62:326-343.
[3] Tao Y, Morrow C T, Heinemann P H, et al. Fourier-based separation technique for shape grading of potatoes using machine vision[J]. Transactions of the ASAE, 1995, 38(3):949-957.
[4] Corrado C, Francesca A, Federico P, et al. Shape analysis of agricultural products: a review of recent research advances and potential application to computer vision[J]. Food Bioprocess Technol, 2011, 4(5):673-692.
[5] Al-Mallahi A, Kataoka T, Okamoto H, et al. An image processing algorithm for detecting in-line potato tubers without singulation[J]. Computers and Electronics in Agriculture, 2010, 70(1):239-244.
[6] Gomes J F S, Leta F R. Application of computer vision techniques in the agriculture and food industry: a review[J]. European Food Research and Technology, 2012, 235(6):989-1000.
[7] Heinemann P H, Pathare N P, Morrow C T. An automated inspection station for machine-vision grading of potatoes[J]. Machine Vision and Applications, 1996, 9(1):14-19.
[8] Patel K K, Kar A, Jha S N, et al. Machine vision system: a tool for quality inspection of food and agricultural products[J]. Journal of Food Science and Technology, 2012, 49(2):123-141.
[9] Tao Y, Heinemann P H, Varghese Z. Machine vision for color inspection of potatoes and apples[J]. Transactions of the ASAE,1995,38(5):1555-1561.
[10] Zhou L, Chalana V, Kim Y. PC-based machine vision for real-time computer-aided potato inspection[J]. International Journal of Imaging Systems and Technology, 1998, 9(6):423-433.
[11] Navid R, Somayeh M B, Soleymani F. A real-time mathematical computer method for potato inspection using machine vision[J]. Computer and Mathematics with Application, 2012, 63(1):268-279.
[12] Gamal E, Sergio C, Enrique M,et al. In-line sorting of irregular potatoes by using automated computer-based machine vision system[J]. Journal of Food Engineering, 2012, 112(1-2):60-68.
[13] 郝敏,麻硕士,郝小冬. 基于Zernike矩的马铃薯形状检测[J]. 农业工程学报,2010,26(2):347-350. Hao Min, Ma Shuo-shi, Hao Xiao-dong. Potato shape detection based on Zernike moments[J]. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(2):347-350.
[14] 周竹,黄懿,李小昱,等. 基于机器视觉的马铃薯自动分级方法[J]. 农业工程学报,2012,28(7):178-183. Zhou Zhu, Huang Yi, Li Xiao-yu, et al. Automatic detecting and grading method of potatoes based on machine vision[J]. Transactions of the Chinese Society of Agricultural Engineering,2012,28(7):178-183.
[15] 郑冠楠,谭豫之,张俊雄,等. 基于计算机视觉的马铃薯自动检测分级[J]. 农业机械学报,2009,40(4):166-168,156. Zheng Guan-nan, Tan Yu-zhi, Zhang Jun-xiong,et al. Automatic detecting and grading method of potatoes with computer vision[J]. Transactions of the CSAM, 2009, 40(4):166-168, 156.
[16] Sun Yi-jun. Iterative RELIEF for feature weighting: algorithms, theories, and application[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(6):1035-1051.
[17] Cortes C,Vapuik V.Soft margin classifier:U.S.Patent 5640492[P].1997-6-17.
[1] CHE Xiang-jiu, WANG Li, GUO Xiao-xin. Improved boundary detection based on multi-scale cues fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1621-1628.
[2] GENG Qing-tian, YU Fan-hua, WANG Yu-ting, GAO Qi-kun. New algorithm for vehicle type detection based on feature fusion [J]. 吉林大学学报(工学版), 2018, 48(3): 929-935.
[3] XU Yan-yan, CHEN Hui, LIU Jia-ju, YUAN Jin-zhao. Cell processor stereo matching parallel computation [J]. 吉林大学学报(工学版), 2017, 47(3): 952-958.
[4] YUAN Zhe-ming, ZHANG Hong-yang, CHEN Yuan. HIV-1 protease cleavage site prediction based on feature selection and support vector machine [J]. 吉林大学学报(工学版), 2017, 47(2): 639-646.
[5] ZHOU Bing-hai, XU Jia-hui. SVM-based real-time scheduling approach of multi-load carries [J]. 吉林大学学报(工学版), 2016, 46(6): 2027-2033.
[6] ZHAO Yun-peng, YU Tian-lai, JIAO Yu-bo, GONG Ya-feng, SONG Gang. Damage identification method and factor evaluation for irregular-shaped bridge [J]. 吉林大学学报(工学版), 2016, 46(6): 1858-1866.
[7] MA Zhi-xing, ZHAO Qi, ZHANG Hao. Fourier analysis model for housekeeping gene [J]. 吉林大学学报(工学版), 2016, 46(5): 1639-1643.
[8] SHEN Xuan-jing, ZHAI Yu-jie, LU Yu-tong, WANG Yu, CHEN Hai-peng. Speaker recognition algorithm based on channel compensation [J]. 吉林大学学报(工学版), 2016, 46(3): 870-875.
[9] SUN Yi-xuan,SHAO Chun-fu,YUE Hao,ZHU Liang. Urban traffic accident severity analysis based on sensitivity analysis of support vector machine [J]. 吉林大学学报(工学版), 2014, 44(5): 1315-1320.
[10] WANG Dan, ZHANG Xiang-he. Biomimetic recognition method of human behavior based on HOG and SVM [J]. 吉林大学学报(工学版), 2013, 43(增刊1): 489-492.
[11] YANG Yan, LIU Sa, LIAN Shi-bin, ZHU Xiao-dong. Analysis of fruit tree pests morphological characteristics based on computer vision [J]. 吉林大学学报(工学版), 2013, 43(增刊1): 235-238.
[12] WANG Xue-jun, ZHAO Lin-lin, WANG Shuang. Video object extraction method based on active learning SVM [J]. 吉林大学学报(工学版), 2013, 43(增刊1): 51-54.
[13] WANG Gang,LIU Yuan-ning,CHEN Hui-ling,DONG Hao,ZHU Xiao-dong,. Application of rough set and support vector machines in hepatitis diagnosis [J]. 吉林大学学报(工学版), 2011, 41(01): 160-0164.
[14] SHANG Fei, MA Jun-Xiao, YAO Li, TIAN Di, QIU Chun-Ling. Multifeature fusion based method for monitoring working status of instruments [J]. 吉林大学学报(工学版), 2010, 40(02): 545-0548.
[15] GE Liang, ZHU Qing-sheng, FU Si-si, LUO Da-jiang, LIU Jin-feng. Improved image dense stereo matching algorithm [J]. 吉林大学学报(工学版), 2010, 40(01): 212-0217.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd