A segmentation algorithm for the automatic recognition of tomato at harvest

Journal of Food, Agriculture and Environment

Volumn 8, Issue 3-4 PART 2, 2010, Pages 815-819

  Arefi, Arman ^a   Motlagh, Asad Modarres ^a   Teimourlou, Rahman Farrokhi ^a  

^a URMIA UNIVERSITY   (Iran)

Author keywords

Algorithm; Image processing; Machine vision; Robot; Tomato

Indexed keywords

ALGORITHM; ARTICLE; CONTROLLED STUDY; FRUIT COLOR; FRUIT GROWTH; FRUIT SIZE; GREENHOUSE; HARVEST; NONHUMAN; PLANT GROWTH; PLANT PARAMETERS; PLANT SEGMENTATION; TOMATO; FRUIT RIPENING; HARVEST PERIOD;

LYCOPERSICON ESCULENTUM;

EID: 78751663264     PISSN: 14590255     EISSN: 14590263     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. Hayashi, S., Ganno, K., Ishii, Y. and Tnaka, I.2002. Robotic harvesting system for eggplants. JARQ 36(3): 163-168.
2. Bulanon, D. M., Kataoka, T., Ota, Y. and Hiroma, T. 2002. A segmentation algorithm for the automatic recognition of Fuji apples at harvest. Biosystems Engineering 83(4):405-412.
3. Feng, G., Qixin, C. and Masateru, N. 2008. Fruit detachment and classification method for strawberry harvesting robot. International Journal of Advanced Robotic System 5:41-48.
4. Philipp, I. and Rath, T. 2002. Processing by use of different colour space transformations. Computers and Electronics in Agriculture 35:1-15.
5. Choi, K., Lee, G., Han, Y. J. and Bunn, J. M. 1995. Tomato maturity evaluation using color image analysis. Transactions of the ASAE 38(1):171-176.
6. Slaughter, D. C. and Harrel, R. H. 1987. Color vision in robotic fruit harvesting. Transactions of the ASAE 30(4): 1144-114.
7. Laykin, S., Alchanatis, V., Fallik, E. and Edan, Y. 2002. Image processing algorithm for tomato classification. Transactions of the ASAE 45(3):851-858.
8. Ohta, Y., Kanade, T. and Sakai, T. 1980. Colour information for region segmentation. Computer Graphics and Image Processing 13:222-241.
9. Woebbecke, D. M., Meyer, G. E., Von Bargen, K. and Mortensen, D. A. 1995. Color indices for weed identification under various soil, residue and lighting conditions. Transactions of the ASAE 38(1):259-269.
10. Wang, Y., Zhu, X. and Ji, C. 2008. Machine vision based cotton recognition for cotton harvesting robot. Computer and Computing Technologies in Agriculture 2:1421-1425.
11. Pietikäinen, M. 1996. Accurate color discrimination with classification based on feature distributions. International Conference on Pattern Recognition, C. pp. 833-838.
12. Littmann, E. and Ritter, H. 1997. Adaptive color segmentation, a comparison of neural and statistical methods. IEEE Trans. Neural Network 8(1):175-185.
13. Cheng, H. D., Jiang, X. H., Sun, Y. and Wang, J. 2001. Color image segmentation: Advances and prospects. Pattern Recognition 34:2259-2281.