Meaningful alignments

Meaningful alignments
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DOI:
10.1023/a:1026593302236
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发表时间:
2000-10-01
影响因子:
19.5
通讯作者:
Morel, JM
Morel, JM
中科院分区:
计算机科学2区
文献类型:
--
作者:
Desolneux, A;Moisan, L;Morel, JM

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我们提出了一种方法来检测图像中的几何结构,没有任何先验信息。粗略地说,如果一个观察到的几何事件在一个随机图像中的发生概率的期望值很小,我们就说这个几何事件是“有意义的”。讨论了该定义的几个问题,通过引入“最大有意义事件”并分析其结构,解决了其中的几个问题。这种方法被应用到检测图像中的对齐。
We propose a method for detecting geometric structures in an image, without any a priori information. Roughly speaking, we say that an observed geometric event is "meaningful" if the expectation of its occurences would be very small in a random image. We discuss the apories of this definition, solve several of them by introducing "maximal meaningful events" and analyzing their structure. This methodology is applied to the detection of alignments in images.