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.
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