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Multi-focus image fusion for accurate measurement of nonwoven structures

机译:多焦点图像融合可精确测量非织造结构

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This paper presents a new region-based image fusion algorithm and its applications for measuring essential parameters of nonwoven structures. The algorithm combines a series of partially focused images of the same sample view captured at different focusing points to form a fully focused image that is fundamental for accurate detections of fiber edges in the structure. It starts with selecting a number of source points based on the maximum gradient matrix, and locating initial fiber boundaries using the pixel-based image fusion algorithm. Within the fiber boundaries, the source points diffuse in the same rate, and the boundaries are formed when their expanding fronts encounter each other. These new boundaries divide the image view into regions of various sizes, each representing a coherent area centered at one source point. Finally, each region is filled with the corresponding region that has the highest average sharpness value among all of the multi-focus images. The paper also presents the experimental results on the fiber diameter, fiber orientation and pore size distributions of nonwovens generated by using this algorithm, in comparison with the results from other methods.
机译:本文提出了一种新的基于区域的图像融合算法及其在非织造结构基本参数测量中的应用。该算法将在不同焦点处捕获的同一样本视图的一系列部分聚焦图像组合在一起,以形成完全聚焦图像,这对于准确检测结构中的光纤边缘至关重要。首先从基于最大梯度矩阵选择多个源点开始,然后使用基于像素的图像融合算法定位初始光纤边界。在光纤边界内,源点以相同的速率扩散,并且边界在它们的扩展前端彼此相遇时形成。这些新边界将图像视图划分为各种大小的区域,每个区域代表以一个源点为中心的连贯区域。最后,在所有多焦点图像中,每个区域都填充有具有最高平均清晰度的相应区域。本文还介绍了使用该算法生成的非织造布的纤维直径,纤维取向和孔径分布的实验结果,并与其他方法的结果进行了比较。

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