Prior-based Hierarchical Segmentation Highlighting Structures of Interest

Amin Fehri, S. Velasco-Forero, F. Meyer
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引用次数: 7

Abstract

Abstract Image segmentation is the process of partitioning an image into a set of meaningful regions according to some criteria. Hierarchical segmentation has emerged as a major trend in this regard as it favors the emergence of important regions at different scales. On the other hand, many methods allow us to have prior information on the position of structures of interest in the images. In this paper, we present a versatile hierarchical segmentation method that takes into account any prior spatial information and outputs a hierarchical segmentation that emphasizes the contours or regions of interest while preserving the important structures in the image. Several applications are presented that illustrate the method versatility and efficiency.
基于先验的分层分割突出感兴趣的结构
摘要图像分割是将图像按照一定的标准划分为一组有意义的区域的过程。分层分割已成为这方面的主要趋势,因为它有利于不同规模的重要区域的出现。另一方面,许多方法允许我们对图像中感兴趣的结构的位置有先验信息。在本文中,我们提出了一种通用的分层分割方法,该方法考虑了任何先验空间信息,并输出分层分割,强调感兴趣的轮廓或区域,同时保留图像中的重要结构。应用实例说明了该方法的通用性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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