Meaningful alignments

被引：282

作者：

Desolneux, A ^{[1
]}

Moisan, L ^{[1
]}

Morel, JM ^{[1
]}

机构：

[1] ENS Cachan, CMLA, F-94235 Cachan, France

来源：

INTERNATIONAL JOURNAL OF COMPUTER VISION | 2000年 / 40卷 / 01期

关键词：

alignment; Gestalt; Helmnoltz; principle; probability;

D O I：

10.1023/A:1026593302236

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：7 / 23

页数：17

共 17 条

[1]

Clare SJ, 1997, THESIS

[2]

Feller W., 1968, INTRO PROBABILITY TH

[3] IMPROVED ASSESSMENT OF SIGNIFICANT ACTIVATION IN FUNCTIONAL MAGNETIC-RESONANCE-IMAGING (FMRI) - USE OF A CLUSTER-SIZE THRESHOLD [J].