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

Color, Size and Shape Feature Extraction Techniques for Fruits: A Technical Review

by Amish Patel, Puja Kadam, Sapan Naik
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 16
Year of Publication: 2015
Authors: Amish Patel, Puja Kadam, Sapan Naik
10.5120/ijca2015906780

Amish Patel, Puja Kadam, Sapan Naik . Color, Size and Shape Feature Extraction Techniques for Fruits: A Technical Review. International Journal of Computer Applications. 130, 16 ( November 2015), 6-10. DOI=10.5120/ijca2015906780

@article{ 10.5120/ijca2015906780,
author = { Amish Patel, Puja Kadam, Sapan Naik },
title = { Color, Size and Shape Feature Extraction Techniques for Fruits: A Technical Review },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 16 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number16/23291-2015906780/ },
doi = { 10.5120/ijca2015906780 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:25:45.268409+05:30
%A Amish Patel
%A Puja Kadam
%A Sapan Naik
%T Color, Size and Shape Feature Extraction Techniques for Fruits: A Technical Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 16
%P 6-10
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Grading of agricultural produce especially the fruits and vegetables has become a perquisite of trading across borders. In India mostly fruit and vegetable growers grade the fruit manually. Manual grading was carried out by trained operators who considered a number of grading factors and fruit were separated according to their physical quality . Manually grading was costly and grading operation was affected due to shortage of labor in peak seasons. Human operations may be inconsistent, less efficient and time consuming. New trends in marketing as specified by World Trade Organization (WTO) demand high quality graded products. Farmers are looking forward to having an appropriate agricultural produce-grading machine in order to alleviate the labor shortage, save time and improve graded product’s quality.. The need to be responsive to market demand places a greater emphasis on quality assessment, resulting in the greater need for improved and more accurate grading and sorting practices. Size variation in vegetables like potatoes, onions provided a base for grading them in different categories. Every vegetable producing country had made their own standards of different grades keeping in view the market requirements.

References
  1. Hatou, K., Morimoto, T., De Jager, J., Hashimoto, Y., 1996. Measurement and recognition of 3-D body in intelligent plant factory. In: Abstracts of the International Conference on Agricultural Engineering (AgEng). Madrid, vol. 2, pp. 861–862 (Paper No. 96F-027)
  2. Aggarwal, J.K., Chien, C.H., 1989. Chapter 2: 3-D structures from 2-D images. In: Sanz, J.L.C. (Ed.), Advances in Machine Vision. Springer-Verlag Inc., New York,NY, pp. 64–121
  3. Affeldt Jr., H.A., Brown, G.K., Brusewitz, G.H., Delwiche, M.J., Hetzroni, A., Kranzler, G.A., et al., 1994. Dimension, shape and surface texture measurement on agricultural commodities. In: Proceedings of the BARD International Workshop on Nondestructive Technologies for Quality Evaluation of Fruits and Vegetables. ASAE, St. Joseph, Mich., USA, pp. 50–62.
  4. 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
  5. S.Arivazhagan, R.Newlin Shebiah, S.Selva Nidhyanandhan, L.Ganesan,” Fruit Recognition usingColor and Texture Features”, Journal of Emerging Trends in Computing and Information Sciences, VOL. 1, NO. 2, pp. 90-94, Oct 2010
  6. 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
  7. 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
  8. 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.
  9. 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
  10. 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
  11. Gall, H., 1997. A ring sensor system using a modified polar coordinate system to describe the shape of irregular objects. Measurement Science and Technology 8 (11), 1228–1235
  12. Besl, P.J., 1989. Chapter 1: active optical range imaging sensors. In: Sanz, J.L.C. (Ed.), Advances in Machine Vision. Springer-Verlag Inc., New York, NY, pp. 1–63
  13. Chalidabhongse, T., Yimyam, P., Sirisomboon, P., 2006. 2-D/3-D vision-based mango’s feature extraction and sorting. In: 9th International Conference on Control, Automation, Robotics and Vision (ICARCV’06), p. 6.
  14. Studman, C.J., 1999. Chapter 3: fruits and vegetables, section 3.3: handling systems and packaging. In: CIGR Handbook of Agricultural Engineering. vol. IV. ASAE, St. Joseph, Mich., USA, pp. 291–339.
  15. 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, October 2010; pp. 90-94.
  16. Agriculture Economics and Importance of Agriculture in National Economy website [Online]
  17. http://agriinfo.in/?page=topic&superid=9&topicid=185.
  18. The Economic Survey 2012-13, Agricultural and ProcessedFood Products Export Development Authority (APEDA) The Union Budget 2013-14, Press Releases, Media Reports website [Online]
  19. http://www.ibef.org/industry/agriculture-india.aspx
  20. Sargent, S.A., Brecht, J.K., Talbot, M.T., Miller, W.M., Chau, K.V., 1988. Performance of
  21. packing line sizers for fresh market tomatoes. ASAE Paper No. 886590. St. Joseph, Mich., ASAE.
  22. 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.
  23. Du, C.-J., Sun, D.-W., 2004. Recent developments in the applications of image processsing techniques for food quality evaluation. Trends in Food Science and Technology 15 (5), 230–249.
  24. T.Morimoto,T.Takeuchi,H.Miyata,Y.Hashimoto,”Pattern recognition of fruit shape based on
  25. the concept of chaos and neural networks”,Computers and Electronics in Agriculture, vol. 26, pp. 171- 186, 2000
  26. 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.
  27. Kazuhiro Nakano,”Application of neural networks to the color grading of apples”, Computers and Electronics in Agriculture, Elsevier, pp. 105-116, 1997.
  28. 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.
  29. Eduardo Carrillo and Alexander Aristizabal Penaloza, "Artificial vision to assure coffee-Excelso beans quality," in EATIS, Czech Republic, pp. 35,2009
Index Terms

Computer Science
Information Sciences

Keywords

Fruit grading Color Feature Extraction Shape Feature Extraction Size Feature Extraction.

Powered by PhDFocusTM