We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Image Processing and Machine Learning for Automated Fruit Grading System: A Technical Review

by Rashmi Pandey, Sapan Naik, Roma Marfatia
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 16
Year of Publication: 2013
Authors: Rashmi Pandey, Sapan Naik, Roma Marfatia
10.5120/14209-2455

Rashmi Pandey, Sapan Naik, Roma Marfatia . Image Processing and Machine Learning for Automated Fruit Grading System: A Technical Review. International Journal of Computer Applications. 81, 16 ( November 2013), 29-39. DOI=10.5120/14209-2455

@article{ 10.5120/14209-2455,
author = { Rashmi Pandey, Sapan Naik, Roma Marfatia },
title = { Image Processing and Machine Learning for Automated Fruit Grading System: A Technical Review },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 16 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number16/14209-2455/ },
doi = { 10.5120/14209-2455 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:14.744919+05:30
%A Rashmi Pandey
%A Sapan Naik
%A Roma Marfatia
%T Image Processing and Machine Learning for Automated Fruit Grading System: A Technical Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 16
%P 29-39
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In India, demand for various fruits and vegetables are increasing as population grows. Automation in agriculture plays a vital role in increasing the productivity and economical growth of the Country, therefore there is a need for automated system for accurate, fast and quality fruits determination. Researchers have developed numerous algorithms for quality grading and sorting of fruit. Color is most striking feature for identifying disease and maturity of the fruit. In this paper; efficient algorithms for color feature extraction are reviewed. Then after, various classification techniques are compared based on their merits and demerits. The objective of the paper is to provide introduction to machine learning and color based grading algorithms, its components and current work reported on an automatic fruit grading system.

References
  1. Agriculture Economics and Importance of Agriculture in National Economy website [Online] http://agriinfo. in/?page=topic&superid=9&topicid=185.
  2. The Economic Survey 2012-13, Agricultural and ProcessedFood Products Export Development Authority (APEDA), The Union Budget 2013-14, Press Releases, Media Reports website [Online] http://www. ibef. org/industry/agriculture-india. aspx
  3. Cunha, J. B. , "Application of image processing techniques in the characterization of plant leafs," Industrial Electronics, 2003. ISIE'03. IEEE International Symposium on, vol. 1, no. , pp. 612, 616 vol. 1, 9-11 June 2003
  4. B. D. Mahaman,M. Maliappis, H. C. Passam c, A. B. Sideridis b, V. Zorkadis d Y. Koumpouros, "Image processing for distance diagnosis in pest management," Computers and Electronics in Agriculture, pp. 121-131, April 2004.
  5. D. W. Lamb and R. B. Brown, "Remote-Sensing and Mapping of Weeds in Crops", J. agric. Engng Res. , pp. 117-125, 27 September 2001.
  6. Tadhg Brosnan and Da-Wen. Sun,"Inspection and grading of agricultural and food products by computer vision systems-a review", Computers and Electronics in Agriculture, pp. 193-213, 2002.
  7. Mr. Viraj A. Gulhane, Dr. Ajay A. Gurjar," Detection of Diseases on Cotton Leaves and Its Possible Diagnosis", International Journal of Image Processing, vol. 5, no. 5,pp. 590-598, 2011.
  8. V. K. Tewari, Ashok Kumar Arudra, Satya Prakash Kumar, Vishal Pandey, Narendra Singh Chandel, "Estimation of plant nitrogen content using digital image processing," International Commission of Agricultural and Biosystems Engineering, vol. 15, no. 2, pp. 78-86, july 2013.
  9. Ercan Ozyildiz, Nils Krahnst-over, Rajeev Sharma," Adaptive texture and color segmentation for tracking moving objects",Pattern recognization, pp. 2013-2029, 2002.
  10. Kanali, C. , Murase, H. , Honami," Three-dimensional shape recognition using a chargesimulation method to process image features", Journal of Agricultural Engineering Research ,pp. 195-208, 1998
  11. F. Pla, F. Juste, "Thinning-based algorithm to characterize fruit stems from profile images", Computers and Electronics in Agriculture, vol. 13, pp. 301-314, 1995.
  12. Kazuhiro Nakano,"Application of neural networks to the color grading of apples", Computers and Electronics in Agriculture, Elsevier, pp. 105-116, 1997.
  13. Naoshi Kondo , Usman Ahmad , Mitsuji Monta ,Haruhiko Murase,"Machine vision based quality evaluation of Iyokan orange fruit using neural networks", Computers and Electronics in Agriculture,vol. 29, pp. 135-147, 2000.
  15. T. Morimoto, T. Takeuchi, H. Miyata, Y. Hashimoto,"Pattern recognition of fruit shape based on the concept of chaos and neural networks",Computers and Electronics in Agriculture, vol. 26, pp. 171-186, 2000.
  16. V. Leemans, H. Mageinb,M. -F. Destain," On-line Fruit Grading according to their External Quality using Machine Vision", Journal of Automation and Emerging Technologies, Belgium. Biosystems Engineering, pp. 397–404, 2002
  17. Woo Chaw Seng and Seyed Hadi Mirisaee, "A New Method for Fruits Recognition System," Electrical Engineering and Informatics, vol. 01, pp. 130-134, August 2009.
  18. Mustafa, N. B. A. ; Ahmed, S. K. ; Ali, Z. ; Yit, W. B. ; Abidin, A. A. Z. ; Sharrif, Z. A. M. , "Agricultural produce Sorting and Grading using Support Vector Machines and Fuzzy Logic," Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on , vol. , no. , pp. 391,396, 18-19 Nov. 2009
  19. Hongshe Dang, Jinguo Song, Qin Guo, "A Fruit Size Detecting and Grading System Based on Image Processing", 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics, vol. 2, pp. 83-86, August 2010.
  20. Eduardo Carrillo and Alexander Aristizabal Penaloza, "Artificial vision to assure coffee-Excelso beans quality," in EATIS, Czech Republic, pp. 35,2009
  21. M. Khojastehnazhand, M. Omid, and A. Tabatabaeefar, "Development of a lemon sorting system based on color and size," African Journal of Plant Science, vol. 4(4), pp. 122-127, April 2010.
  22. Xu Liming and Zhao Yanchao, "Automated strawberry grading system based on image processing," Computers and Electronics in Agriculture, vol. 71, no. Supplement 1, pp. S32-S39, April 2010.
  23. Yousef Al Ohali, "Computer vision based date fruit grading system: Design and implementation," Journal of King Saud University - Computer and Information Sciences, vol. 23, no. 1, pp. 29-39, January 2011
  24. S. Arivazhagan, R. Newlin Shebiah, S. Selva Nidhyanandhan, L. Ganesan," Fruit Recognition using Color and Texture Features", Journal of Emerging Trends in Computing and Information Sciences, VOL. 1, NO. 2, pp. 90-94, Oct 2010.
  25. Tajul Rosli Bin Razak, Mahmod Bin Othman(DR), Mohd Nazari Bin Abu Bakar(DR), Khairul Adilah BT Ahmad, and AB. Razak Bin Mansor, "Mango Grading By Using Fuzzy Image Analysis,"In proceedings of International Conference on Agricultural, Environment and Biological Sciences, Phuket, 2012.
  26. Dong Zhang, Kirt D. Lillywhite, Dah-Jye Lee, Beau J. Tippetts, Automated apple stem end and calyx detection using evolution-constructed features, Journal of Food Engineering, Volume 119, Issue 3, December 2013, Pages 411-418, ISSN 0260-8774.
  27. V. Leemans and M. F. Destain, "A real-time grading method of apples based on features extracted from defects," Journal of Food Engineering, vol. 61, no. 1, pp. 83-89, January 2004.
  28. Xu Qiabao, Zou Xiaobo, and Zhao Jiewen, "On-Line Detection of Defects on Fruit by Machinevision Systems Based on Three-Color-Cameras Systems," Computer and Computing Technologies in Agriculture II, vol. 3, pp. 2231-2238, 2009.
  29. P. Levi, R. Falla, R. Pappalardo, "Image controlled robotics applied to citrus fruit harvesting. Procedures", ROVISEC-VII, Zurich, 1988.
  30. D. Slaughter, R. C. Harel," Color vision in robotic fruit harvesting", Trans. ASAE 30 (4) (1987) 1144,1148.
  31. F. Juste, F. Sevilla, Citrus: A European project to study the robotic harvesting of oranges, in: Proc. 3rd Int. Symp. Fruit, Nut and Vegetable Harvesting Mechanization, Denmark, Sweden, Norway, 1991, pp. 331,338.
  32. Whitaker, Miles, Mitchell and Gaultney, Fruit location in a partially occluded image, Trans. ASAE 30 (3) (1987)591,597.
  33. F. Buemi, M. Massa, G. Sandini, AGROBOT: a robotic system for greenhouse operations, in: Proc. 4th Worksop on Robotics in Agriculture & the Food Industry, IARP, Toulouse, 1995, pp. 172,184.
  34. Dah-Jye Lee, James K. Archibald, and Guangming Xiong, "Rapid Color Grading for Fruit Quality Evaluation Using Direct Color Mapping," IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, vol. 8, no. 2, pp. 292-302, November 2011
  35. Md. Rokunuzzaman, H. P. W. Jayasuriya," Development of a low cost machine vision system for sorting of tomatoes", CIGR Journal, Vol. 15, No. 1,pp. 173-180,2013.
  36. Hong Zheng and Hongfei Lu, "A least-squares support vector machine (LS-SVM) based on fractal analysis and CIELab parameters for the detection of browning degree on mango (Mangifera indica L. )," Computers and Electronics in Agriculture, vol. 83, pp. 47-51, January 2012.
  37. Guo Feng and Cao Qixin," Study on Color Image Processing Based Intelligent Fruit Sorting System", Proceedings of the 5" World Congress on Intelligent Control and Automation, pp. 4802-4805, June 15-19, 2004.
  38. I. Kavd?r and D. E. Guyer, "Comparison of Artificial Neural Networks and Statistical Classifiers in Apple Sorting using Textural Features," Journal of Biosystems Engineering, pp. 331–344, November 2004.
  39. Zou Xiaobo, Zhao Jiewen, and Li Yanxiao, "Apple color grading based on organization feature parameters," Pattern Recognition Letters, vol. 28, pp. 2046-2053, June 2007.
  40. P. Sudhakara Rao and S. Renganathan," New Approaches for Size Determination of Apple Fruits for Automatic Sorting and Grading", iranian journal of electrical and computer engineering, Vol. 1, No. 2, November, 2002.
  41. J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, "Citrus sorting by identification of the most common defects using multispectral computer vision," Journal of Food Engineering, vol. 83, no. 3, pp. 384-393, December 2007.
  42. M. Z. Abdullah, J. Mohamad-Saleh, A. S. Fathinul-Syahir,B. M. N. Mohd Azemi,"Discrimination and classification of fresh-cut starfruits(Averrhoa carambola L. ) using automated machine vision system", Journal of Food Engineering ,pp. 506–523,2006.
  43. Norasyikin Fadilah, Junita Mohamad-Saleh, Zaini Abdul Halim, Haidi Ibrahim and Syed Salim Syed Ali ," Intelligent Color Vision System for Ripeness Classification of Oil Palm Fresh Fruit Bunch", pp. 14179-14195,2012.
  44. Changyong Li, Qixin Cao, and Feng Guo," A method for color classification of fruits based on machine vision", WTOS 8, vol. 2, pp. 312-321, February, 2009.
  45. Shivleela R Arlimatti," Window Based Method for Automatic Classification of Apple Fruit", International Journal of Engineering Research and Applications ,Vol. 2, Issue 4, pp. 1010-1013, July-August 2012.
  46. Dae Gwan Kim, Thomas F. Burks, Jianwei Qin, Duke M. Bulanon," Classification of grapefruit peel diseases using color texture feature analysis", International Journal of Agricultural and Biological Engineering ,Vol. 2, No. 3,pp. 41-50,September,2009.
  47. J. I. Asnor, S. Rosnah, Z. W. H. Wan, and H. A. B. Badrul," Pineapple Maturity Recognition Using RGB Extraction",World Academy of Science,Engineering and Technology,vol. 78 ,pp. 147-150,2013.
  48. Bernard Gosselin,Olivier Kleynen, Vincent Leemans, Marie-France Destain and Olivier Debeir Devrim Unay, "Automatic grading of Bi-colored apples by multispectral machine vision," Computers and Electronics in Agriculture, November 2010.
  49. Haiwei Dong and Nikolaos Mavridis Abdulhamid Haidar, "Image-Based Date Fruit Classification," International Congress on Ultra Modern Telecommunications and Control Systems, vol. IV, 2012.
  51. Bernard Gosselin and Devrim Unay, "Thresholding based segmentation and apple grading by machine vision".
  52. Yifei Xu, Li Li , Xiaoli Li, Yong He Shuiguang Deng, "A feature-selection algorithm based on Support Vector Machine-Multiclass for hyperspectral visible spectral analysis," Journal of Food Engineering, May 2013.
  53. Micheline Kamber Jiawei Han, Data Mining:Concepts and Techniques, 2nd ed. : Morgan Kaufmann.
  54. Gonzalo Pajares, Xavier P. Burgos-Artizzu, Angela Ribeiro Alberto Tellaeche, "A computer vision approach for weeds identification through Support Vector Machine," Applied Soft Computing, pp. 908–915, 2011.
  55. D. S. Jayas, J. Paliwal, and N. S. Visen, "Multi-layer Neural Networks for Image Analysis of Agricultural Products," Silsoe Research Institute, 2000.
  56. Zhiqing Wen and Yang Tao, "Building a rule-based machine-vision system for defect inspection on apple sorting and packing lines," Expert Systems with Applications, pp. 307–313, 1999.
Index Terms

Computer Science
Information Sciences

Keywords

Fruit grading Machine learning Color feature extraction Classification

Powered by PhDFocusTM