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Vision-Based On-Loom Measurement of Yarn Densities in Woven Fabrics

机译:基于视觉的机织机织纱线密度在线测量

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摘要

A vision-based measurement system to quantify the yarn density of woven fabrics during production is presented. As an extension to an earlier developed fabric flaw detection system, the proposed framework consists of a combination of basic and custom-made image-processing techniques that allow to precisely track single wefts and warps within fabric images—in real-time. Several adaptations facilitate the measurement of density changes for plain, satin, and twill weaves. In this paper, the algorithmic framework has been evaluated in several comprehensive on-line experiments on a real-world air-jet loom and is additionally compared with three alternative methods for fabric density measurement. It proved to be precise, robust, and applicable for industrial use as it overcomes many of the existing shortcomings of current methods.
机译:提出了一种基于视觉的测量系统,可以量化生产过程中机织织物的纱线密度。作为对较早开发的织物瑕疵检测系统的扩展,提出的框架由基本和定制的图像处理技术组成,可以实时精确地跟踪织物图像中的单纬和经纱。多种调整有助于测量平纹,缎纹和斜纹组织的密度变化。在本文中,该算法框架已在现实世界中的喷气织机上进行了数次全面的在线实验,并已与三种用于测量织物密度的替代方法进行了比较。由于它克服了当前方法的许多现有缺点,因此被证明是精确,可靠且可用于工业用途。

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