Profiled fiber cross‐sectional shape characterization for identification

Abstract

Purpose -The purpose of this paper is to show how shape analysis and quantitative characterization of fiber cross sections, with the aid of image analysis techniques, provide a quick, powerful approach to automated profiled fiber identification. Design/methodology/approach -In this paper, an effective method of cross-sectional shape characterization for profiled fiber identification is reported with extraction of the distance fluctuation curve of fiber cross-sectional boundary to the centroid. By calculating their cross-correlations using signal processing techniques, the authors tackle the problem of calibrating the starting points of fiber objects orientated arbitrarily in image successfully, which are difficult to deal with by means of image processing, to finish the normalization of distance fluctuation curves. For two fiber cross-sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves. Findings -Based on this, the method presented extracts the curves of all fiber cross-sections in one sample, compares the similarity degrees between each other, and creates clusters to identify profiled fiber. Originality/value -Experimental results validate that this curve can effectively characterize profiled fiber cross-sectional contour for profiled fiber identification and the normalization method is feasible.