Yet another survey on image segmentation:: Region and boundary information integration
Yet another survey on image segmentation:: Region and boundary information integration
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DOI：
10.1007/3-540-47977-5_27
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发表时间：
2002-01-01
期刊：
影响因子：
--
通讯作者：
Cufí, X
中科院分区：
文献类型：
--
作者：
Freixenet, J;Muñoz, X;Cufí, X
图像分割一直是计算机视觉中的一个相关研究领域，在过去的30年中已经提出了数百种分割算法。然而，众所周知，基于边界或区域信息的元素分割技术往往不能产生准确的分割结果。因此，在过去的几年中，有一种趋势，即利用这种信息的互补性的算法。本文综述了融合边缘和区域信息的各种分割方案，并重点介绍了7种融合边缘和区域信息的不同策略和方法。其他调查仅描述和比较不同的定性方法，与此相反，本调查涉及真实的定量比较。在这个意义上，关键的方法已经编程和他们的精度分析和比较使用合成和真实的图像。文中给出了与实验结果相一致的讨论，并给出了可在因特网上获得的代码.
Image segmentation has been, and still is, a relevant research area in Computer Vision, and hundreds of segmentation algorithms have been proposed in the last 30 years. However, it is well known that elemental segmentation techniques based on boundary or region information often fail to produce accurate segmentation results. Hence, in the last few years, there has been a tendency towards algorithms which take advantage of the complementary nature of such information. This paper rewiews different segmentation proposals which integrate edge and region information and highlights 7 different strategies and methods to fuse such information. In contrast with other surveys which only describe and compare qualitatively different approaches, this survey deals with a real quantitative comparison. In this sense, key methods have been programmed and their accuracy analyzed and compared using synthetic and real images. A discussion justified with experimental results is given and the code is available on Internet.