The.Algorithm.Design.Manual.Springer-Verlag.1998
The.Algorithm.Design.Manual.Springer-Verlag.1998 The.Algorithm.Design.Manual.Springer-Verlag.1998
Simplifying Polygons Next: Shape Similarity Up: Computational Geometry Previous: Polygon Partitioning Algorithms Mon Jun 2 23:33:50 EDT 1997 file:///E|/BOOK/BOOK5/NODE195.HTM (4 of 4) [19/1/2003 1:31:55]
Shape Similarity Next: Motion Planning Up: Computational Geometry Previous: Simplifying Polygons Shape Similarity Input description: Two polygonal shapes, and . Problem description: How similar are and ? Discussion: Shape similarity is a problem that underlies much of pattern recognition. Consider a system for optical character recognition (OCR). We have a known library of shape models representing letters and the unknown shapes we obtain by scanning a page. We seek to identify an unknown shape by matching it to the most similar shape model. The problem of shape similarity is inherently ill-defined, because what ``similar'' means is application dependent. Thus no single algorithmic approach can solve all shape matching problems. Whichever method you select, expect to spend a large chunk of time tweaking it so as to achieve maximum performance. Don't kid yourself - this is a difficult problem. Among your possible approaches are: ● Hamming Distance - Assume that your two polygons have been overlaid one on top of the other. The Hamming distance measures the area of symmetric difference between the two polygons, in file:///E|/BOOK/BOOK5/NODE196.HTM (1 of 3) [19/1/2003 1:31:56]
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Shape Similarity<br />
Next: Motion Planning Up: Computational Geometry Previous: Simplifying Polygons<br />
Shape Similarity<br />
Input description: Two polygonal shapes, and .<br />
Problem description: How similar are and ?<br />
Discussion: Shape similarity is a problem that underlies much of pattern recognition. Consider a system<br />
for optical character recognition (OCR). We have a known library of shape models representing letters<br />
and the unknown shapes we obtain by scanning a page. We seek to identify an unknown shape by<br />
matching it to the most similar shape model.<br />
<strong>The</strong> problem of shape similarity is inherently ill-defined, because what ``similar'' means is application<br />
dependent. Thus no single algorithmic approach can solve all shape matching problems. Whichever<br />
method you select, expect to spend a large chunk of time tweaking it so as to achieve maximum<br />
performance. Don't kid yourself - this is a difficult problem.<br />
Among your possible approaches are:<br />
● Hamming Distance - Assume that your two polygons have been overlaid one on top of the other.<br />
<strong>The</strong> Hamming distance measures the area of symmetric difference between the two polygons, in<br />
file:///E|/BOOK/BOOK5/NODE196.HTM (1 of 3) [19/1/2003 1:31:56]