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Analysis of Guava Quality by Image Processing

by Matheus Pedroza Ferreira, Glêndara A. De S. Martins, Warley Gramacho Da Silva
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 3
Year of Publication: 2016
Authors: Matheus Pedroza Ferreira, Glêndara A. De S. Martins, Warley Gramacho Da Silva
10.5120/ijca2016912404

Matheus Pedroza Ferreira, Glêndara A. De S. Martins, Warley Gramacho Da Silva . Analysis of Guava Quality by Image Processing. International Journal of Computer Applications. 156, 3 ( Dec 2016), 30-36. DOI=10.5120/ijca2016912404

@article{ 10.5120/ijca2016912404,
author = { Matheus Pedroza Ferreira, Glêndara A. De S. Martins, Warley Gramacho Da Silva },
title = { Analysis of Guava Quality by Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 3 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 30-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number3/26691-2016912404/ },
doi = { 10.5120/ijca2016912404 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:01:37.272741+05:30
%A Matheus Pedroza Ferreira
%A Glêndara A. De S. Martins
%A Warley Gramacho Da Silva
%T Analysis of Guava Quality by Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 3
%P 30-36
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Brazil is an important fruit producer in the world. Despite the enormous production, fruit classification techniques do not follow the requirements of consumer protection institutions regarding food quality, since visual and manual classification techniques are still widely used. In this way, the development of machinery and grading systems has been increasingly exploited in order to meet the market's demands. The objective of the present study is to develop a system capable of identifying defects on the guava surface to determine its degree of quality.

References
  1. Agência Sebrae. 2009. Brasil é o terceiro maior produtor de frutas do mundo. Disponível em http://www.canalrural.com.br/canalrural/jsp/default.jsp?uf=1&local=1&action=noticias&id=2535814&section=noticias. Acesso em 06/03/2014
  2. Rodrigues, J.C.; Filho, J.M.L. Análise de qualidade de frutas por imagens multiespectrais. Revista Científica Eletrônica UNISEB, v.1, n.1, 91 – 110p., 2013.
  3. Panigrahi, S.; Gunasekaran, S. Computer vision. In: GUNASEKARAN, S. (Ed.). Nondesctructive food evaluation: techniques to analyze properties and quality. New York: Marcel Dekker, 2001. p. 39–98.
  4. Brodie, J. R., Hansen, A. C., and Reid, J. F. (1994). Size assessment of stacked logs via the Hough Transform. Transactions of the ASAE, 37(1), 303–310.
  5. Dıaz, R., Faus, G., Blasco, M., Blasco, J., and Molto, E. (2000). The application of a fast algorithm for the classification of olives by machine vision. Food Research International, 33, 305–309.
  6. Aleixos, N., Blasco, J., Navarron, F., and Molto, E. (2002). Multispectral inspection of citrus in real-time using machine vision and digital signal processors. Computers and Electronics in Agriculture, 33(2), 121–137.
  7. Leemans, V., Destain, M. F. (2004). A real-time grading method of apples based on features extracted from defects. Journal of Food Engineering, 61(1), 83–89.
  8. Gonzalez, R. C., Woods, R. E. (2002). Digital image processing. NJ, USA: Prentice Hall.
  9. Aleixos, N., Blasco, J., and Molto´ , E. (1999). Design of a vision system for real-time inspection of oranges. In VIII national symposium on pattern recognition and image analysis (pp. 387–394). Bilbao, Spain.
  10. J. Blasco, N. Aleixos, E. Molto (2006). Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm.
  11. Yining Deng, Charles Kenney, Michael S. Moore and B. S. Manjunath (1999). PEER GROUP FILTERING AND PERCEPTUAL COLOR IMAGE QUANTIZATION. Department of Electrical and Computer Engineering, University of California.
  12. M. Emre Celebi (2011) .Improving the Performance of K-Means for Color Quantization. Department of Computer Science, Louisiana State University.
  13. Yining Deng and B. S. Manjunath (2001). Unsupervised Segmentation of Color-Texture Regions in Images and Video.
  14. J. Astola, P. Haavisto, and Y. Neuvo, “Vector median filters”, Proc. of IEEE, vol. 78, p. 678-89, April, 1990.
  15. C. Kenney, Y. Deng, B. S. Manjunath, and G. Hewer (2001) .Peer Group Image Enhancement.
  16. R.O. Duda and P.E. Hart, Pattern classification and scene analysis, John Wiley & Sons, New York, 1970.
  17. S. Lloyd, Least Squares Quantization in PCM, IEEE Trans. on Information Theory 28 (2) (1982) 129–136.
  18. S. Wan, P. Prusinkiewicz, S. Wong, Variance-Based Color Image Quantization for Frame Buffer Display, Color Research and Application 15 (1) (1990) 52–58.
  19. Cofilab, (2014). Image database ‘Apple Golden’. Retrieved from : http://www.cofilab.com/portfolio/goldendb/
Index Terms

Computer Science
Information Sciences

Keywords

Guava Quality Classification System applied.

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