Size estimation of sweet onions using consumer-grade RGB-depth sensor

Journal of Food Engineering

Volumn 142, Issue , 2014, Pages 153-162

  Wang, Weilin ^a   Li, Changying ^a  

^a University of Georgia   (United States)

Author keywords

Kinect; Machine vision; Phenotyping; RBG D; Size estimation; Volume

Indexed keywords

COMPUTER VISION;

KINECT; PHENOTYPING; RBG-D; SIZE ESTIMATION; VOLUME;

SENSORS;

EID: 84904015167     PISSN: 02608774     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfoodeng.2014.06.019     Document Type: Article

References (20)

1. J. Blasco, N. Aleixos, and E. Moltó Machine vision system for automatic quality grading of fruit Biosyst. Eng. 85 4 2003 415 423 (Pubitemid 36996530)
2. J.L. Brewster Onions and Other Vegetable Alliums 2008 CABI Cambridge, MA, USA
3. Canessa, A., Chessa, M., Gibaldi, A., Sabatini, S.P., Solari, F., 2013. Calibrated depth and color cameras for accurate 3D interaction in a stereoscopic augmented reality environment. Journal of Visual Communication and Image Representation.
4. Y. Chéné, D. Rousseau, P. Lucidarme, J. Bertheloot, V. Caffier, P. Morel, É. Belin, and F. Chapeau-Blondeau On the use of depth camera for 3D phenotyping of entire plants Comput. Electron. Agric. 82 2012 122 127
5. C.L.M. de Visser, and W. van den Berg A method to calculate the size distribution of onions and its use in an onion growth model Sci. Hortic. 77 3-4 1998 129 143 (Pubitemid 28501680)
6. B. Freedman, A. Shpunt, M. Machline, and Y. Arieli Depth Mapping Using Projected Patterns 2010 Prime Sense Ltd. USA
7. H. Gall, A. Muir, J. Fleming, R. Pohlmann, L. GÃļcke, and W. Hossack A ring sensor system for the determination of volume and axis measurements of irregular objects Meas. Sci. Technol. 9 11 1998 1809 1820
8. Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D., 2010. RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments.
9. K. Imou, Y. Kaizu, M. Morita, and S. Yokoyama Three-dimensional shape measurement of strawberries by volume intersection method Trans. ASABE 49 2 2006 449 456 (Pubitemid 43774033)
10. V. Iraguen, A. Guesalaga, and E. Agosin A portable non-destructive volume meter for wine grape clusters Meas. Sci. Technol. 17 12 2006 N92 N96
11. K. Khoshelham, and S.O. Elberink Accuracy and resolution of kinect depth data for indoor mapping applications Sensors 12 2 2012 1437 1454
12. A.B. Koc Determination of watermelon volume using ellipsoid approximation and image processing Postharvest Biol. Technol. 45 3 2007 366 371 (Pubitemid 47088252)
13. A. Laurentini The visual hull concept for silhouette-based image understanding Pattern Anal. Mach. Intell. IEEE Trans. 16 2 1994 150 162
14. D.J. Lee, X. Xu, J. Eifert, and P. Zhan Area and volume measurements of objects with irregular shapes using multiple silhouettes Opt. Eng. 45 2 2006 027202
15. C. Mallor, M. Balcells, F. Mallor, and E. Sales Genetic variation for bulb size, soluble solids content and pungency in the Spanish sweet onion variety Fuentes de Ebro. Response to selection for low pungency Plant Breeding 130 1 2011 55 59
16. Microsoft, 2010. Kinect. http://www.xbox.com/en-us/kinect/ (accessed on 10.15.13).
17. G.P. Moreda, J. Ortiz-Cañavate, F.J. García-Ramos, and M. Ruiz-Altisent Non-destructive technologies for fruit and vegetable size determination - a review J. Food Eng. 92 2 2009 119 136
18. A.Y. Mulayim, U. Yilmaz, and V. Atalay Silhouette-based 3-D model reconstruction from multiple images IEEE Trans. Syst. Man Cybern. Part B Cybern.: A Publ. IEEE Syst. Man Cybern. Soc. 33 4 2003 582 591
19. U.S. Department of Agriculture, 1995. United States Standards for Grades of Onions (Other than Bermuda-Granex-Grano and Creole Type). U.S. Department of Agriculture.
20. Wang, Q., Zhang, Q., 2013. Three-dimensional reconstruction of a dormant tree using RGB-D cameras. In: 2013 Annual International Meeting of the American Society of Agricultural and Biological Engineers, Kansas City, Missouri.