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Proceedings Paper

Determining composition of grain mixtures using texture energy operators
Author(s): Bradley Pryor Kjell
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Paper Abstract

Images of texture may be convolved with a set of small operators to produce texture energy features for classification or for image segmentation. These operators are usually picked from a standard set, such as Laws' texture energy operators or the variations discussed by other researchers. In this paper, texture energy features are used to determine the percentage composition of mixtures of rice and barley. The grains of white rice and pearled barley are similar in size and reflectivity, and hundreds of overlapping grains appear in each image. This problem is representative of many visual inspection tasks. Two approaches are used: multi- linear regression, and linear classification into discrete composition classes. The texture energy features used are standard Laws' operators in two sizes, and operators found through a stochastic optimization procedure.

Paper Details

Date Published: 1 November 1992
PDF: 6 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992);
Show Author Affiliations
Bradley Pryor Kjell, Central Connecticut State Univ. (United States)

Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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