The.Algorithm.Design.Manual.Springer-Verlag.1998

The.Algorithm.Design.Manual.Springer-Verlag.1998 The.Algorithm.Design.Manual.Springer-Verlag.1998

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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]

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]

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