Estimation of filament orientation in three dimensional CT image of textile fabric based on principal component analysis

T. Shinohara
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引用次数: 1

Abstract

In this paper, a method to estimate a filament orientation is proposed in a three dimensional computer tomography (3D CT) image of a textile fabric for a structure analysis. In this study, yarn positional information is obtained as the structure analysis of the textile fabric by using the estimated filament orientation at each voxel of the 3D CT image. In previous study, the filament orientation was estimated by correlating a filament model, which is cylindrical solid model, with the 3D CT image. Since the maximum value of the correlation is calculated by an iterative calculation method, an extraordinary amount of time is required to estimate the filament orientation over the 3D CT image. In this paper, a different approach to estimate the filament orientation is proposed in order to shorten the processing time: a principal component analysis-based method is proposed. The axis of the first principal component is regarded as the filament orientation. The validity of the proposed method is confirmed by experimentally applying the proposed method to actual textile fabric. The effectiveness of the proposed method is then indicated by comparing the processing times of the filament orientation estimation by the proposed and previous methods.
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基于主成分分析的纺织织物三维CT图像中长丝方向估计
本文提出了一种用于织物结构分析的三维计算机断层扫描(3D CT)图像中纤维方向的估计方法。在本研究中,利用三维CT图像中每个体素处估计的长丝方向,获得纱线位置信息作为纺织织物的结构分析。在之前的研究中,通过将灯丝模型(圆柱实体模型)与三维CT图像相关联来估计灯丝的方向。由于相关性的最大值是通过迭代计算方法计算的,因此需要大量的时间来估计3D CT图像上的灯丝方向。为了缩短加工时间,本文提出了一种不同的方法来估计长丝取向:基于主成分分析的方法。第一主成分的轴线被认为是灯丝的方向。将该方法应用于实际纺织织物,验证了该方法的有效性。然后,通过比较所提方法和先前方法的灯丝取向估计的处理时间,表明所提方法的有效性。
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