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Reseach Article

Quality evaluation of apple fruit: A Survey

by Komal Sindhi, Jaymit Pandya, Sudhir Vegad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 1
Year of Publication: 2016
Authors: Komal Sindhi, Jaymit Pandya, Sudhir Vegad
10.5120/ijca2016908340

Komal Sindhi, Jaymit Pandya, Sudhir Vegad . Quality evaluation of apple fruit: A Survey. International Journal of Computer Applications. 136, 1 ( February 2016), 32-36. DOI=10.5120/ijca2016908340

@article{ 10.5120/ijca2016908340,
author = { Komal Sindhi, Jaymit Pandya, Sudhir Vegad },
title = { Quality evaluation of apple fruit: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 1 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number1/24119-2016908340/ },
doi = { 10.5120/ijca2016908340 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:35:53.058247+05:30
%A Komal Sindhi
%A Jaymit Pandya
%A Sudhir Vegad
%T Quality evaluation of apple fruit: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 1
%P 32-36
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Disease recognition has been huge research area nowadays because inspection of quality of fruits at an early stage prevents spreading of disease to the other areas of fruit as well as helps to reduce great economic losses in agricultural sectors and industries. Different types of diseases exist in different fruits. The focus of the present research work is on quality evaluation of apple fruit. The basic process for defect detection in fruits is basically divided into two major steps; feature extraction and classification .Feature extraction involves extracting features like color, texture and shape from fruit image. The output of this are feature vectors which are given as an input to the classifier. Finally, the classifier categorizes them into appropriate classes. The accuracy of this process depends on many factors like number of input images, method chosen for pre processing, features extracted, classifier chosen, etc.

References
  1. IndiaRankinAgriculturehttp://www.apeda.gov.in/apedawebsite/six_head_product/FFV.htm
  2. India’srankinappleproductionhttp://www.whichcountry.co/top-10-apple-producing-countries-in-the-world.
  3. Shiv Ram Dubey, Anand Jhalal , “Adapted Approach for Fruit Disease Identification using Images” International Journal of Computer Vision and Image Processing (IJCVIP) 2, no. 3, 2014.
  4. Hartman, J. (2010, April). Apple Fruit Diseases Appearing at Harvest. Plant Pathology Fact Sheet, College of Agriculture, University of Kentucky.
  5. Applescabfactsheethttp://nysipm.cornell.edu/factsheets/treefruit diseases/as/as.asp.
  6. Marie-France Destain “ Defect segmentation of ‘golden delicious’ apples using colour machine vision’ , Computer and Electronics in Agriculture,1998.
  7. V. Leemans , M.-F. Destain, “A real-time grading method of apples based on features extracted from defects, Elsevier , 2004.
  8. Devrim Unay, Bernard Gosselin, “Artificial neural network-based segmentation and apple grading by Machine vision “, IEEE ,2005.
  9. Bin Zhu, Lu Jiang, “Gabor feature-based apple quality inspection using kernel principal component analysis” ,Elsevier ,2007.
  10. K. Vijayarekha “Multivariate image analysis for defect identification of apple fruit image”, IEEE ,2008.
  11. Jin-jing Wang, De-an Zhao, Wei Ji,” Application of Support Vector Machine to Apple Recognition using in Apple Harvesting Robot”, IEEE International Conference on Information and Automation, 2009.
  12. Rade L. Radojević1, Dragan V. Petrović1,” Digital parameterization of apple fruit size, shape and surface spottiness “,African Journal of Agricultural Research Vol. 6(13), pp. 3131-3142, 4 July, 2011.
  13. Devrim Unay , Bernard Gosselin , “Automatic grading of Bi-colored apples by multispectral machine vision”,Elsevier ,2011.
  14. Armin Ghabousian, Mousa Shamsi, “Segmentation of Apple Color Images Utilizing Fuzzy Clustering Algorithms”,Advances in Digital Multimedia, March,2012.
  15. A. Gopal , R. Subhasree, Venkatesh. K. Srinivasan,” Classification of Color Objects like Fruits using Probability Density Function (PDF)”,IEEE ,2012.
  16. Shivleela R Arlimatti ,” Window Based Method for Automatic Classification of Apple Fruit”, International Journal of Engineering Research and Applications, Vol. 2, Issue 4, July-August 2012, pp.1010-1013.
  17. Dubey, S. R., & Jalal, A. S. ,” Detection and Classification of Apple Fruit Diseases using Complete Local Binary Patterns”. In Proceedings of the 3rd International Conference on Computer and Communication Technology ,2012.
  18. Rushikesh Borse, Monica Jhuria ,” Image processing for smart farming: detection of disease and fruit grading “, Proceedings of the 2013 IEEE International Conference on Image Information Processing(ICIIP-2013).
  19. Vani Ashok ,Dr. D.S. Vinod, “Automatic Quality Evaluation of Fruits Using Probabilistic Neural Network Approach”, IEEE ,2014.
  20. Shiv Ram Dubey, Anand Singh Jalal , “Apple disease classification using color, texture and shape features from images, Springer,2015.
  21. S.Janardhana, Dr.J.Jaya, “Computer Aided Inspection System For Food Products Using Machine Vision – A Review”, International Conference on Current Trends in Engineering and Technology, ICCTET,2013.
  22. Dong ping Tian, “A Review on Image Feature Extraction and Representation Techniques”, International Journal of Multimedia and Ubiquitous Engineering Vol. 8, No. 4, July, 2013.
  23. Vijay Satti, “An automatic leaf recognition System for plant Identification using machine Vision technology”, International journal of engineering science and technology, vol. 5 no.04, April 2013.
  24. Saswati Naskar, Tanmay Bhattacharya, “A Fruit Recognition Technique using Multiple Features and Artificial Neural Network”, International Journal of Computer Applications (0975 – 8887) Volume 116 – No. 20, April 2015.
  25. Ch.Srinivasa Rao, S.Srinivas Kumar,” Content Based Image Retrieval using exact Legendre moments and support vector machine” ,International Journal of Multimedia and its applications”, May,2010.
Index Terms

Computer Science
Information Sciences

Keywords

Digital image processing Quality Evaluation apple disease feature extraction classification