DocumentCode :
595306
Title :
An accurate and contrast invariant junction detector
Author :
Gui-Song Xia ; Delon, Julie ; Gousseau, Yann
Author_Institution :
CEREMADE, Univ. Paris-Dauphine, Paris, France
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2780
Lastpage :
2783
Abstract :
This paper introduces a generic method for the accurate analysis of junctions, relying on a statistical modeling of normalized image gradients. We analyze junctions as local visual events that do not happen by chance under a background model derived from the a-contrario methodology. The method not only provides thresholds for the detection of junctions, but also enables their accurate characterization, including a precise computation of their type, localization, scale and geometrical configuration. The efficiency of the method is evaluated through various experiments.
Keywords :
gradient methods; object detection; statistical analysis; acontrario methodology; background model; contrast invariant junction detector; generic method; junction analysis; junction characterization; local visual events; normalized image gradients; statistical modeling; Accuracy; Computational modeling; Detectors; Junctions; Pattern recognition; Random variables; Semiconductor counters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460742
Link To Document :
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