Determining diameter of animal textile fiber using image processing techniques

Abstract

In the context of productive sustainability of animal textile fibers, the possibility to achieve safe and inexpensive methods allowing to measure fiber quality is paramount for farmers pretending to compete in local and international markets. Using an image of a longitudinal cut of camelid fibers, we propose a computational method in which a Hierarchical Temporary Memory algorithm recognizes and identifies each of these fibers and a modified Gabor filter enhances and reconstructs the input image in order to reduce measurement errors of the mean diameter due to crossovers and out of focus objects. In this paper this procedure is described and results are discussed. The obtained results agree with the laboratory measurements.