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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 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.

@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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