Cotton Color Grading with a Neural Network

Abstract

It is well known that disagreements about cotton color grades between high volume instruments and classers are substantial, and these machine-classer disagreements deter full acceptance of machine grading of cotton color. This paper provides first a quantitative analysis of the distributions of these disagreements across all the color grades, both major and subcolor categories. The study proves that the disagreements can be both systematic and random, and further analyzes the possible sources for them. Second, the paper introduces a novel design of a neural network classifier for cotton color classification. This classifier consists of multiple networks performing a two-step classification that identifies major and subcolor categories separately. The classifier can be trained by any desirable data. In this research, it is trained using a set of classers' grades, and it exhibits good generalization for the new testing data. The classifier seems to reduce machine-classer disagreements to a minimal level, which is limited by the classer's reproducibility.

Fundamentals of soft models in textiles

“…Implementing the Kalman filter algorithm to training a neural network to evaluate the grade of wrinkled fabrics using the angular second moment, contrast, correlation, entropy, and fractal dimension obtained by image analysis is described in [73]. The neural network classifier for cotton color using a two-step classification that identifies major and sub-color categories separately is presented in [74]. Neural network modeling was successfully applied to creating the relationship between the scanner device-dependent color space and the device-independent CiE color space [85].…”

Artificial Neural Networks and Their Applications in the Engineering of Fabrics

“…One of the most typical problems of the animal fibres classification has been faced using Artificial Neural Networks (She et al, 2002). In the case of cotton, ANNs have been used for the grading of the color of the raw fibres (Cheng et al, 1999;Xu et al, 2000;Kang et al, 2002). An attempt for the classification of the cotton lint has been also based on the use of ANNs (Mwasiagi et al, 2009).…”

Digieye Application In Cotton Colour Measurement

“…Colour is a basic criterion that determines the quality classification of cotton raw materials according to the Universal Cotton Standards, which is globally accepted and routinely used in many countries as the standard for US and non-US grown cottons [4,8,16,20,21].…”