Title :
Scale-Space Behavior of Planar-Curve Corners
Author :
Zhong, Baojiang ; Ma, Kai-Kuang ; Liao, Wenhe
Author_Institution :
Dept. of Math., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
Abstract :
The curvature scale-space (CSS) technique is suitable for extracting curvature features from objects with noisy boundaries. To detect corner points in a multiscale framework, Rattarangsi and Chin investigated the scale-space behavior of planar-curve corners. Unfortunately, their investigation was based on an incorrect assumption, viz., that planar curves have no shrinkage under evolution. In the present paper, this mistake is corrected. First, it is demonstrated that a planar curve may shrink nonuniformly as it evolves across increasing scales. Then, by taking into account the shrinkage effect of evolved curves, the CSS trajectory maps of various corner models are investigated and their properties are summarized. The scale-space trajectory of a corner may either persist, vanish, merge with a neighboring trajectory, or split into several trajectories. The scale-space trajectories of adjacent corners may attract each other when the corners have the same concavity, or repel each other when the corners have opposite concavities. Finally, we present a standard curvature measure for computing the CSS maps of digital curves, with which it is shown that planar-curve corners have consistent scale-space behavior in the digital case as in the continuous case.
Keywords :
curve fitting; edge detection; feature extraction; CSS trajectory map; feature extraction; multiscale framework; noisy boundary; planar-curve corner detection; scale-space behavior; shrinkage effect; standard curvature measure; CSS; Computer vision; Scale space; Shape; corner detection; curvature; curve evolution; digital curves; discrete curvature; dual trajectory.; evolution trajectory; shrinkage rate;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Conference_Location :
12/12/2008 12:00:00 AM
DOI :
10.1109/TPAMI.2008.295