Using colour features of cv. 'Gala' apple fruits in an orchard in image processing to predict yield

Precision Agriculture

Volumn 13, Issue 5, 2012, Pages 568-580

  Zhou, Rong ^b   Damerow, Lutz ^a   Sun, Yurui ^a,b   Blanke, Michael M ^a  

^a UNIVERSITY OF BONN   (Germany)

^b CHINA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Apples; Colour; Image analysis; Image processing; Modelling; Yield prediction

Indexed keywords

ALGORITHM; COLOR MORPH; COMPUTER; CROP YIELD; DATA SET; FRUIT; IMAGE PROCESSING; ORCHARD; RIPENING;

BONN; GERMANY; NORTH RHINE-WESTPHALIA;

MALUS X DOMESTICA;

EID: 84866010233     PISSN: 13852256     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11119-012-9269-2     Document Type: Article

References (14)

1. Aggelopoulou, A. D., Bochtis, D., Fountas, S., Swain, K. C., Gemtos, T. A., & Nanos, G. D. (2011). Yield prediction in apple orchards based on image processing. Precision Agriculture, 12, 448-456.
2. Blanke, M. M. (2011). Prediction of apple yields in Europe-present and new approaches in research. In L. Smith (Ed.), Proceedings 106th annual meeting Washington state horticultural association (pp. 68-75). Yakima, WA: WSHA Publishing.
3. Bulanon, D. M., Burks, T. F., & Alchanatis, V. (2009). Fruit visibility analysis for robotic citrus harvesting. Transactions of the ASABE, 52(1), 277-283.
4. Bulanon, D. M., Kataoka, T., Ota, Y., & Hiroma, T. (2002). A segmentation algorithm for the automatic recognition of fuji apples. Biosystems Engineering, 83, 405-412.
5. Chinchuluun, R., & Lee, W. S. (2006). Citrus yield mapping system in natural outdoor scenes using the watershed transform. Paper No. 063010. St. Joseph, MI: ASABE.
6. Damerow, L., & Blanke, M. M. (2008). A new device for precision and selective flower thinning to regulate fruit set and improve fruit quality. In R. Ehsani, & G. Albrigo (Eds.), Proceedings of international symposium on application of precision agriculture for fruits and vegetables. Acta Horticulturae, 824, 275-281.
7. Perry, E. M., Dezzani, R. J., Seavers, C., & Pierce, F. J. (2010). Spatial variation in tree characteristics and yield in a pear orchard. Precision Agriculture, 11, 42-60.
8. Rakun, J., Stajnko, D., & Zazzula, D. (2011). Detecting fruits in natural scenes by using spatial-frequency based texture analysis and multiview geometry. European Journal of Horticultural Science: Gartenbauwissenschaft, 76, 80-88.
9. Si, Y. S., Qiao, J., Liu, G., Liu, Z. X., & Gao, R. (2009). Recognition and shape features extraction of apples based on machine vision. Transactions of the Chinese Society for Agricultural Machinery, 40(8), 161-165.
10. Stajnko, D., Lakota, M., & Hocevar, M. (2004). Estimation of number and diameter of apple fruits in an orchard during the growing season by thermal imaging. Computers and Electronics in Agriculture, 42, 31-42.
11. Stajnko, D., Rakun, J., & Blanke, M. M. (2009). Modelling apple fruit yield using image analysis for fruit colour, shape and texture. European Journal of Horticultural Science: Gartenbauwissenschaft, 74(6), 260-267.
12. Wachs, J. P., Sturm, H. J., Burks, F., & Akhanais, V. (2010). Low and high-level visual feature-based apple detection from multi-modal images. Precision Agriculture, 11, 717-735.
13. Winter, F. (1986). Modelling the biological and economic development of an apple orchard. Acta Horticulturae, 160, 353-360.
14. Zhang, Y. J., Li, M. Z., Qiao, J., & Liu, G. (2008). Segmentation algorithm for apple recognition using image features and artificial neural network. Acta Optica Sinica, 28(11), 2104-2108.