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首页> 外文期刊>The Journal of the Textile Institute. 1, Fibre Science and Textile Technology >Textile Woven-fabric Recognition by Using Fourier Image-analysis Techniques Part Ⅰ: A Fully Automatic Approach for Crossed-points Detection
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Textile Woven-fabric Recognition by Using Fourier Image-analysis Techniques Part Ⅰ: A Fully Automatic Approach for Crossed-points Detection

机译：傅里叶图像分析技术识别织物机织物的第一部分：交叉点检测的全自动方法

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摘要

One of the major problems in automatic woven-fabric recognition is how to detect the areas of interlacing warp and weft yarns. This problem is termed 'crossed-points detection'. With a non-periodic design, such as flowers, which may sometimes occur over a woven-fabric background, the problem of crossed-points detection becomes very difficult. In this work, we propose a new and fully automatic method based on Fourier image-analysis techniques. The application of this method to simple woven fabric, as well as to fabric with skewness or with non-periodic design, demonstrates the ability to solve such crossed-points-detection problems. Finally the algorithm is evaluated visually by superposing the detected grid image on the initial woven-fabric image. All the detected crossed-points are displayed independently and may be saved as file-format images for further processing.
机译：机织物自动识别的主要问题之一是如何检测经纱和纬纱交织的区域。这个问题被称为“交叉点检测”。对于非周期性的设计，例如花朵，有时可能会在织物背景上出现，交叉点检测的问题变得非常困难。在这项工作中，我们提出了一种基于傅立叶图像分析技术的新型全自动方法。该方法在简单的机织织物上以及偏斜或非周期性设计的织物上的应用证明了解决此类交叉点检测问题的能力。最终，通过将检测到的网格图像叠加在初始机织织物图像上进行视觉评估。所有检测到的交叉点将独立显示，并可保存为文件格式图像以进行进一步处理。

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