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Objective Evaluation of the Trash and Color of Raw Cotton by Image Processing and Neural Network

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Authors
KANG, TAE JIN; KIM, SOO CHANG
Issue Date
2002-09
Publisher
SAGE Publications
Citation
Textile Res. J. 72(9), 776-782
Abstract
The trash and color of raw cotton are very important and decisive factors in the current
cotton grading system. In this paper, an image system is developed that can characterize
trash from a raw cotton image captured by a color CCD camera and acquire color
parameters. The number of trash particles and their content, size, size distribution, and spatial
density can be evaluated after raw cotton images of the physical standards are thresholded and
connectivity is checked. The color grading of raw cotton can be influenced by trash if the
image of raw cotton includes trash. Therefore, the effect of trash on color grading is
investigated using a color difference equation that measures the color difference between a
trash-containing image and a trash-removed image. Color grading of raw cotton involves a
trained artificial neural network, which turns out to have a good classifying ability, suggesting
that the application of an artificial neural network for color grading is highly valid.
ISSN
0040-5175
Language
English
URI
https://hdl.handle.net/10371/12422
DOI
https://doi.org/10.1177/004051750207200905
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Material Science and Engineering (재료공학부) Journal Papers (저널논문_재료공학부)
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