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Reseach Article

Automatic Segmentation and Yield Measurement of Fruit using Shape Analysis

by H. N. Patel, R.k.jain, M.v.joshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 7
Year of Publication: 2012
Authors: H. N. Patel, R.k.jain, M.v.joshi
10.5120/6792-9119

H. N. Patel, R.k.jain, M.v.joshi . Automatic Segmentation and Yield Measurement of Fruit using Shape Analysis. International Journal of Computer Applications. 45, 7 ( May 2012), 19-24. DOI=10.5120/6792-9119

@article{ 10.5120/6792-9119,
author = { H. N. Patel, R.k.jain, M.v.joshi },
title = { Automatic Segmentation and Yield Measurement of Fruit using Shape Analysis },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 7 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number7/6792-9119/ },
doi = { 10.5120/6792-9119 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:58.519780+05:30
%A H. N. Patel
%A R.k.jain
%A M.v.joshi
%T Automatic Segmentation and Yield Measurement of Fruit using Shape Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 7
%P 19-24
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Efficient locating the fruit on the tree is one of the major requirements for the fruit harvesting system. In this paper, automatic segmentation and yield calculation of fruit based on shape analysis is presented. Color and shape analysis was utilized to segment the images of different fruits like apple, pomegranate, oranges, peach, litchi and plum obtained under different lighting conditions. First the input sectional tree image was converted from RGB colour space into the L*a*b colour space. The resultant image was then applied to the algorithm for fruit segmentation. The Edge detection and combination of a circular fitting algorithm was used for the automatic segmentation of fruit in the image. The resultant edge points were then used for fitting the approximate circular shape. The resultant fitted circles were used as a count of total number of fruits in an image. Hundred sectional tree images of different fruits were used for the segmentation and yield measurement. The results indicate that the proposed method can accurately segment the occluded fruits with the efficiency of 98% and the average yield measurement error was found as 31. 4 %.

References
  1. Arivazhagan S. , Newlin Shebiah R. , Nidhyanandhan Selva S. , Ganesan L. , " Fruit Recognition using Color and Texture Features", Journal of Emerging Trends in Computing and Information Sciences, vol. 1, no. 2, Pages: 90-94, Oct 2010.
  2. Bulanon D. M. , Burks T. F. , Alchanatis V. , "Image Fusion of visible and thermal images for fruit segmentation", Biosystems Engineering, Vol-103, Issue-1, May 2009, pages: 12-22.
  3. Bulanon D. M. , Burks T. F. and Alchanatis V. , " Study of temporal variation in citrus canopy using thermal imaging for citrus fruit segmentation", Biosystems Engineering, Vol-101, Issue 2, Pages 161-171, October 2008.
  4. Bulanon D. M. , Burks T. F. , Alcahnatis V. , "Improving Fruit segmentation for robotic fruit harvesting", ISHS Acta Horticulturae 824: International Symposium on Application of Precision Agriculture for Fruits and Vegetables.
  5. Blasco J. , Aleixos N. , Molto E. , " Machine Vision System for Automatic Quality Grading of Fruit", Biosystems Engineering , Vol-85, Issue 4, Pages-415-423, August 2003.
  6. Fernández, L. , Castillero, C. and Aguilera, J. M. , "An application of image analysis to dehydration of apple discs" Journal of Food Engineering, vol. 67, pp. 185-193, 2005.
  7. Hannan M. W. , Burks T. F. , Bulanon D. M. , "A Machine Vision Algorithm for Orange Fruit Segmentation", Agricultural Engineering International: the CIGR E journal, vol-XI, Pages: 1-7, December-2009.
  8. Hayashi Shigehiko, Ota Tomohiko, Kubota Kotaro, Ganno Katsunobu and Kondo Naoshi, "Robotic Harvesting Technology for Fruit Vegetables in Protected Horticultural Production", Information and Technology for Sustainable Fruit and Vegetable Production FRUTIC 05, France.
  9. Jimenez A. R. , Ceres R. , Pons J. L. , "A Survey of Computer Vision Methods for Locating Fruit on Trees", Transaction of the ASAE, Vol. 43(6), pages: 1911-1920, 2000.
  10. Jimenez R. , Jain A. K. , Ceres R. , Pons J. L. , "Automatic fruit recognition: A survey and new results using Range/Attenuation images", Pattern Recognition, 32 (10), pp. 1719-1736, 1999.
  11. Lopez Jose J. , Cobos Maximo and Aguilera Emanuel, "Computer-based segmentation and classification of flaws in citrus fruits", Internation conference on natural image processing (ICONIP-2009).
  12. Leemans, V. and Destain, M. -F, "A real-time grading method of apple based on features extracted from defects" Journal of Food Engineering, vol. 61, pp. 83-89, 2004.
  13. Patel Hetal,Jain R. K. , Joshi M. V. ,"Fruit Detection using improved multiple feature based algorithm", International Journal on Computer Applications(ISSN: 0975 – 8887)", Vol-13, No-2, pages:1-5,January,2011.
  14. Parvati K. , Prakasa Rao B. S. and Das Mariya M. , "Image Segmentation using Gray-scale Morphology and Marker-controlled Watershed Transformation", Hindawi Publishing Corporation, Discrete Dynamics in Nature and Society, Vol-2008, pages;1-8.
  15. Shasi Buluswar , "Models for Outdoor Color Vision", Doctoral dissertation, University of Massachusetts, Amherst,2002
  16. Woo Chaw Seng and Seyed Hadi Mirisaee, "A New Method for Fruits Recognition System", MNCC Transactions on ICT, Vol. 1, No. 1, June 2009.
  17. Zhao, J. T. , J. Katupitiya, J. , "On-tree fruit recognition using texture properties and color data", International conference on Intelligent Robots and Systems, pp. 263-268, 2005.
  18. A. Hanbury and J. Serra. "Mathematical Morphology in the CIELAB space. ", Image Analysis and Stereology, 21(3) : 201-206, 2002 .
  19. S. Dai and Y. Zhang. "Colour image segmentation with watershed on colour histogram and Markov random fields",Information , Communication and Signal Processing, 1:527-531, 2003.
  20. V. Pratt, "Direct least-squares fitting of algebraic surfaces", computer graphics, vol-21, pp 145-152 ,1987.
Index Terms

Computer Science
Information Sciences

Keywords

L*a*b Color Space Edge Detection Circular Fitting