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Objective Evaluation of the Trash and Color of Raw Cotton by Image Processing and Neural Network
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Web of Science
Cited 49 time in Scopus
- Authors
- 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
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