Short communication. Computer vision applied to saffron flower (Crocus sativus L.) processing
Abstract
This paper presents a computer vision system to obtain, using image analysis, the optimal cutting point of saffron flowers in order to obtain their stigmas. For this purpose, an effective and flexible computer program has been developed to process the flower image in order to obtain the cutting point to be sent to the cutting element. Furthermore, experimentation with real saffron flowers has been carried out in order to validate the developed application. In particular, the tests show that the method has good robustness and high success percentage in the flower characterization regardless the shape and size of the flower. The high image processing rate of the proposed method (20 computations s–1) would allow to greatly increase the production rate obtained with an automated cutting system compared to that obtained with the traditional hand method.
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References
Abdel-Aziz Y., Karara H., 1971. Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry. Papers from the American Society of Photogrammetry, Symposium on Close-Range Photogrammetry, Urbana, ILL, USA, pp. 1-18.
Blasco J., Cubero-García S., Alegre-Sosa S., Goméz-Sanchís J., López-Rubira V., Moltó-García E., 2008. Short communication. Automatic inspection of the pomegranate (Punica granatum L.) arils quality by means of computer vision. Span J Agric Res 6(1), 12-16.
Dougherty E.R., 1992. An introduction to morphological image processing. SPIE Optical Engineering Press, Bellingham, Washington.
Fu K.S., Gonzalez R.C., Lee C.S.G., 1987. Robotics control, sensing, vision and intelligence. McGraw-Hill, NY, USA.
Huang Y., Lee F., 2010. An automatic machine visionguided grasping system for Phalaenopsis tissue culture plantlets. Comput Electron Agr 70(1), 42-51. http://dx.doi.org/10.1016/j.compag.2009.08.011
ICEX/Estacom database. Spanish Institute of Foreign Trade/Foreign Trade Database. http://www.icex.es.
Niblack W., 1986. An introduction to digital image processing. Prentice Hall, NJ, USA.
Omid M., Khojastehnazhand M., Tabatabaeefar A., 2010. Estimating volume and mass of citrus fruits by image processing technique. J Food Eng 100(2), 315-321. http://dx.doi.org/10.1016/j.jfoodeng.2010.04.015
Premkumar K., Thirunavukkarasu C., Abraham S.K., Santhiya S.T., Ramesh A., 2006. Protective effect of saffron (Crocus sativus L.) aqueous extract against genetic damage induced by anti-tumor agents in mice. Human Exp Toxicol 25(2), 79-84. http://dx.doi.org/10.1191/0960327106ht589oa PMid:16539212
Rakun J., Stajnko D., Zazula D., 2011. Detecting fruits in natural scenes by using spatial-frequency based texture analysis and multiview geometry. Comput Electron Agr. 76 (1), 80-88. http://dx.doi.org/10.1016/j.compag.2011.01.007
Rocha A., Hauagge D.C., Wainer J., Goldenstein S., 2010. Automatic fruit and vegetable classification from images. Comput Electron Agr 70(1), 96-104. http://dx.doi.org/10.1016/j.compag.2009.09.002
Story D., Kacira M., Kubota C., Akoglu A., An L., 2010. Lettuce calcium deficiency detection with machine vision computed plant features in controlled environments. Comput Electron Agr 74(2), 238-243. http://dx.doi.org/10.1016/j.compag.2010.08.010
Swain K.C., Zaman Q.U., Schumann A.W., Percival D.C., Bochtis D.D., 2010. Computer vision system for wild blueberry fruit yield mapping. Biosyst Eng 106(4), 389-394. http://dx.doi.org/10.1016/j.biosystemseng.2010.05.001
Unay D., Gosselin B., Kleynen O., Leemans V., Destain M.F., Debeir O., 2011. Automatic grading of Bi-colored apples by multispectral machine vision. Comput Electron Agr 75(1), 204-212. http://dx.doi.org/10.1016/j.compag.2010.11.006
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