Scale-based detection of corners of planar curves
Rattarangsi, A.
Chin, R.T.
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Apr 1992
Volume: 14,
Issue: 4
On page(s): 430-449
ISSN: 0162-8828
References Cited: 22
CODEN: ITPIDJ
INSPEC Accession Number: 4166327
Digital Object Identifier: 10.1109/34.126805
Current Version Published: 2002-08-06
Abstract
A technique for detecting and localizing corners of planar curves
is proposed. The technique is based on Gaussian scale space, which
consists of the maxima of absolute curvature of the boundary function
presented at all scales. The scale space of isolated simple and double
corners is first analyzed to investigate the behavior of scale space due
to smoothing and interactions between two adjacent corners. The analysis
shows that the resulting scale space contains line patterns that either
persist, terminate, or merge with a neighboring line. Next, the scale
space is transformed into a tree that provides simple but concise
representation of corners at multiple scales. Finally, a multiple-scale
corner detection scheme is developed using a coarse-to-fine tree parsing
technique. The parsing scheme is based on a stability criterion that
states that the presence of a corner must concur with a curvature
maximum observable at a majority of scales. Experiments were performed
to show that the scale space corner detector is reliable for objects
with multiple-size features and noisy boundaries and compares favorably
with other corner detectors tested
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