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F. Mokhtarian and Alan K. Mackworth. Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(1):34–43, 1986. 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.]
The problem of finding a description, at varying levels ofdetail, for planar curves and matching two such descriptions is posedand solved in this paper. A number of necessary criteria are imposedon any candidate solution method. Path-based Gaussian smoothingtechniques are applied to the curve to find zeros of curvature at varyinglevels of detail. The result is the "generalized scale space" image of aplanar curve which is invariant under rotation, uniform scaling andtranslation of the curve. These properties make the scale space imagesuitable for matching. The matching algorithm is a modification of theuniform cost algorithm and finds the lowest cost match of contours inthe scale space images. It is argued that this is preferable to matchingin a so-called stable scale of the curve because no such scale may existfor a given curve. This technique is applied to register a Landsat satelliteimage of the Strait of Georgia, B.C. (manuall corrected for skew)to a map containing the shorelines of an overlapping area.
@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 <I>Computer Vision: Advances and Applications</I>,
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 ={},
}
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