Cotton Color Classification by Fuzzy Logic

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.