Determining Wheat Vitreousness Using Image Processing and a Neural Network

Transactions of the American Society of Agricultural Engineers

Volumn 46, Issue 4, 2003, Pages 1143-1150

  Wang, N ^a,c   Dowell, F E ^b   Zhang, N ^a  

^a Sunflower Networking Group   (United States)

^b KANSAS STATE UNIVERSITY   (United States)

^c MCGILL UNIVERSITY   (Canada)

Author keywords

Durum wheat; Grading; Grain; HSI color space; Inspection; Machine vision; Neural network; Vitreousness

Indexed keywords

ALGORITHMS; BACKPROPAGATION; CROPS; IMAGE PROCESSING;

GRAINS;

NEURAL NETWORKS;

ALGORITHM; CLASSIFICATION; IMAGE PROCESSING; INSTRUMENTATION; NEURAL NETWORK; REAL TIME METHOD; WHEAT;

TRITICUM AESTIVUM; TRITICUM TURGIDUM SUBSP. DURUM;

EID: 0242287220     PISSN: 00012351     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. Delwiche, S. R, Y. Chen, and W. R. Hruschka. 1995. Differentiation of hard red wheat by near-infrared analysis of bulk samples. Cereal Chemistry 72(3): 243-247.
2. Dexter, J. E., and B. A. Marchylo. 2000. Recent trends in durum wheat milling and pasta processing: Impact on durum wheat quality requirements. Presented at the International Workshop on Durum Wheat, Semolina, and Pasta Quality. Montpellier, France. 27 November 2000. Vienna, Austria: The International Association of Cereal Science and Technology (ICC - Europe).
3. Dexter, J. E., P. C. Williams, N. M. Edwards, and D. G. Martin. 1988. The relationships between durum wheat vitreousness, kernel hardness, and processing quality. J. Cereal Science 7: 169-181.
4. Dowell, F. E. 2000. Differentiating vitreous and nonvitreous durum wheat kernels by using near-infrared spectroscopy. Cereal Chemistry 77(2): 155-158.
5. Egelberg, P., O. Mansson, and C. Peterson. 1994. Assessing cereal grain quality with a fully automated instrument using artificial neural network processing of digitized color video images. In Proc. SPIE International Symposium on Optics in Agriculture, Forestry, and Biological Processing. Boston, Mass. 2-4 November 1994. SPIE 2345: 146-158.
6. Gonzalez, R. C., and R. E. Woods. 1992. Digital Image Processing. Boston, Mass.: Addison-Wesley.
7. GrainCheck 310. 1999. User's Guide. Version 3.5. Lund, Sweden: AgroVision AB.
8. Martin, C. R., R. Rousser, and D. L. Brabec. 1993. Development of a single-kernel wheat characterization system. Trans. ASAE 36(5): 1399-1404.
9. Sissons, M. J., B. G. Osborne, R. A. Hare, S. A. Sissons, and R. Jackson. 2000. Application of the single-kernel characterization system to durum wheat testing and quality prediction. Cereal Chemistry 77(2): 4-10.
10. Steenhoek, L. W., M. K. Misra, C. R. Hurburgh Jr., and C. J. Bern. 2001. Implementing a computer vision system for corn kernel damage evaluation. Applied Eng. in Agric. 17(2): 235-240.
11. Svensson, E., P. Egelberg, C. Peterson, and R. Oste. 1996. Image analysis in grain quality control. In Proc. Nordic Cereal Congress - The Nordic Cereal Industry towards Year 2000, 74-83. 12-15 May 1996. Haugesund, Norway. Nordic Cereal Association.