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Proceedings Paper

Image texture analysis of crushed wheat kernels
Author(s): Inna Y. Zayas; C. R. Martin; James L. Steele; Richard E. Dempster
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Paper Abstract

The development of new approaches for wheat hardness assessment may impact the grain industry in marketing, milling, and breeding. This study used image texture features for wheat hardness evaluation. Application of digital imaging to grain for grading purposes is principally based on morphometrical (shape and size) characteristics of the kernels. A composite sample of 320 kernels for 17 wheat varieties were collected after testing and crushing with a single kernel hardness characterization meter. Six wheat classes where represented: HRW, HRS, SRW, SWW, Durum, and Club. In this study, parameters which characterize texture or spatial distribution of gray levels of an image were determined and used to classify images of crushed wheat kernels. The texture parameters of crushed wheat kernel images were different depending on class, hardness and variety of the wheat. Image texture analysis of crushed wheat kernels showed promise for use in class, hardness, milling quality, and variety discrimination.

Paper Details

Date Published: 1 March 1992
PDF: 13 pages
Proc. SPIE 1615, Machine Vision Architectures, Integration, and Applications, (1 March 1992); doi: 10.1117/12.58828
Show Author Affiliations
Inna Y. Zayas, USDA/U.S. Grain Marketing Research Lab. (United States)
C. R. Martin, USDA/U.S. Grain Marketing Research Lab. (United States)
James L. Steele, USDA/U.S. Grain Marketing Research Lab. (United States)
Richard E. Dempster, USDA/U.S. Grain Marketing Research Lab. (United States)


Published in SPIE Proceedings Vol. 1615:
Machine Vision Architectures, Integration, and Applications
Bruce G. Batchelor; Michael J. W. Chen; Frederick M. Waltz, Editor(s)

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