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An Improved Multivariate Image Analysis Method for Quality Control of Nanofiber Membranes

机译:一种改进的纳米纤维膜质量控制的多变量图像分析方法

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摘要

Multivariate image analysis is a widely used technique for computing a spatial statistical characterization of an image. In this paper a modified method for multivariate image analysis is presented. The proposed method reformulates the approach previously presented by Bharati et al. [2004] extending its range of applicability by reducing its computational complexity and its memory requirements: this allows to take into consideration a larger set of spatial statistics to characterize the image texture. The proposed approach is applied to a case study concerning the estimation of the fiber diameter distribution in nanostructured membranes. The results suggest that the optimum range of spatial statistics used for characterizing the image is related to the size of the main textural features.
机译:多变量图像分析是用于计算图像的空间统计表征的广泛使用的技术。本文介绍了一种用于多变量图像分析的修改方法。所提出的方法重新制定了先前由Bharati等人呈现的方法。 [2004]通过降低其计算复杂性及其内存要求来扩展其适用性范围:这允许考虑到更大的空间统计数据来表征图像纹理。所提出的方法适用于关于纳米结构膜中纤维直径分布估计的案例研究。结果表明,用于表征图像的最佳空间统计范围与主要纹理特征的大小有关。

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