Cotton Color Classification by Fuzzy Logic
- 1 June 2002
- journal article
- research article
- Published by SAGE Publications in Textile Research Journal
- Vol. 72 (6), 504-509
- https://doi.org/10.1177/004051750207200607
Abstract
This paper describes the application of fuzzy logic to cotton color grading in an attempt to improve the acceptance of machine grading for cotton colors. Cotton color grades are a number of classes in the (Rd, b) color space. Adjacent color classes have blurry and overlapping boundaries, making crisp-boundary methods ineffective for cotton color classification. Fuzzy logic is specialized to deal with uncertainty and imprecision in the decision-making process, and thus offers a new approach for grading cotton colors. In this paper, we present the procedures for constructing a fuzzy inference system (FIS) using fuzzy logic to classify major classes of cotton colors, and the preliminary results to demonstrate FIS effectiveness in reducing machine-classer disagreements in color grading. The results from the Fis show great consistency for multiple year of cotton color data.Keywords
This publication has 2 references indexed in Scilit:
- Cotton Color Grading with a Neural NetworkTextile Research Journal, 2000
- Investigating New Factors in Cotton Color GradingTextile Research Journal, 1998