TY - GEN
T1 - An accurate and contrast invariant junction detector
AU - Xia, Gui Song
AU - Delon, Julie
AU - Gousseau, Yann
PY - 2012/12/1
Y1 - 2012/12/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84874562765
M3 - Conference contribution
AN - SCOPUS:84874562765
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2780
EP - 2783
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -