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dr-jts committed Feb 28, 2025
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* <p>
* This algorithm is an approximation to the standard Hausdorff distance.
* Specifically,
* <pre>
* for all geometries a, b: DHD(a, b) &lt;= HD(a, b)
* </pre>
* <blockquote>
* <i>for all geometries A, B: DHD(A, B) &lt;= HD(A, B)</i>
* </blockquote>
* The approximation can be made as close as needed by densifying the input geometries.
* In the limit, this value will approach the true Hausdorff distance:
* <pre>
* DHD(A, B, densifyFactor) -&gt; HD(A, B) as densifyFactor -&gt; 0.0
* </pre>
* <blockquote>
* <i>DHD(A, B, densifyFactor) &rarr; HD(A, B) as densifyFactor &rarr; 0.0</i>
* </blockquote>
* The default approximation is exact or close enough for a large subset of useful cases.
* Examples of these are:
* <ul>
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* </pre>
* The class can compute the oriented Hausdorff distance from A to B.
* This computes the distance to the farthest point on A from B.
* <blockquote>
* <i>OHD(A, B) = max<sub>a &isin; A</sub>( Distance(a, B) )</i>
* <br>
* with
* <br>
* <i>HD(A, B) = max( OHD(A, B), OHD(B, A) )</i>
* </blockquote>
* A use case is to test whether a geometry A lies completely within a given
* distance of another one B.
* This is more efficient than testing whether A is covered by a buffer of B.
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