用于纹理或噪声图像分割和轮廓闭合的高尺度边缘研究

F. Huet, S. Philipp
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引用次数: 1

摘要

在大规模应用时,基于Canny方法的边缘检测器提供的边缘在图像的无噪声和无纹理区域定位良好,但在其他区域的边缘数量过多。本文的目的是研究这些高尺度边缘,特别是它们的局部密度。高尺度边缘是通过特征的方式来研究的,这些特征表征了各种情况,如纹理区域,有噪声或无噪声的物体边界对应的轮廓。这些特征甚至可以表征各种纹理。这些特征可以用来建立纹理/噪声区域的地图,然后执行分割方法合作。另一个应用是轮廓闭合,使用纹理之间的距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-scale edge study for segmentation and contour closing in textured or noisy images
When they are used in a high-scale way, the edge detectors based on Canny's approach provide edges which are well localized in non-noisy and non-textured areas of the image, but which are too numerous in other areas. The aim of this paper is to study these high-scale edges, especially their local density. High-scale edges are studied by the way of features which characterize various situations such as texture areas, contours corresponding to object frontiers with or without noise. Such features may even characterize various textures. These features may be used to build a map of textured/noisy areas and then to perform a segmentation method cooperation. Another application is the contour closing, using distances between textures.
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