Algorithm for measuring fiber length distributions of raw cotton and combed wool using dual-beard image method

Abstract

The dual-beard image method, which has been developed in recent years as a fast and economical method for fiber length measurement, consists of dual-beard specimen preparation, image processing, fibrogram extraction, and length parameter calculations. However, one of the shortcomings of this method is that it can only produce extremely limited length parameters such as mean length, coefficient of variation, modal length, and quality length (UHML, upper half mean length). This study introduces a new algorithm for converting the dual-beard fibrogram into a length distribution histogram which can be used to calculate most of the current length parameters. The algorithm is based on the short fiber content formulae but modified by theoretical analysis and experimental comparison. The length distributions of 24 cotton samples and 12 wool samples are measured by dual-beard image method with the new algorithm, and Advanced Fiber Information System (AFIS) and Almeter are employed for comparison. Comparative analysis shows that the peaks and ranges of the distribution histograms using the dual-beard method are similar to those from the reference methods, and the shapes of histograms from difference methods match well with one another. In addition, five length parameters calculated from the dual-beard distributions are verified to be consistent with those measured by AFIS and Almeter. The new algorithm employed in the dual-beard image method avoids the differential operation which amplifies the curve error, giving the dual-beard image method the ability to output more comprehensive length information.