@COMMENT This file was generated by bib2html.pl version 0.94
@COMMENT written by Patrick Riley
@COMMENT This file came from Alan K. Mackworth's publication pages at
@COMMENT http://www.cs.ubc.ca/~mack/publications
@Article{IEEE-PAMI86,
author = {F. Mokhtarian and Alan K. Mackworth},
title = {Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes},
year = {1986},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {8},
number = {1}
pages = {34--43},
note = {Reprinted in *Computer Vision: Advances and Applications*,
R. Kasteri and R. C. Jain (eds.), IEEE Computer Society Press,
Los Alamitos, CA, 1992, pp. 154-163. [Selected on basis of high citation
frequency.]},
abstract = {The problem of finding a description, at varying levels of
detail, for planar curves and matching two such descriptions is posed
and solved in this paper. A number of necessary criteria are imposed
on any candidate solution method. Path-based Gaussian smoothing
techniques are applied to the curve to find zeros of curvature at varying
levels of detail. The result is the "generalized scale space" image of a
planar curve which is invariant under rotation, uniform scaling and
translation of the curve. These properties make the scale space image
suitable for matching. The matching algorithm is a modification of the
uniform cost algorithm and finds the lowest cost match of contours in
the scale space images. It is argued that this is preferable to matching
in a so-called stable scale of the curve because no such scale may exist
for a given curve. This technique is applied to register a Landsat satellite
image of the Strait of Georgia, B.C. (manuall corrected for skew)
to a map containing the shorelines of an overlapping area.
},
bib2html_pubtype ={Refereed Journal},
bib2html_rescat ={},
}