Polygon Matching and Indexing Under Affine Transformations
This work addresses computational geometry challenges for applications like image processing or pattern recognition, offering incremental improvements in algorithmic efficiency for polygon matching.
The paper tackles the problem of efficiently matching and indexing polygons under affine transformations, presenting algorithms that achieve query times independent of collection size for similarity transformations and O(n+log(m)) time for known affine transformations, with specific bounds for triangles in noisy conditions.
Given a collection $\{Z_1,Z_2,\ldots,Z_m\}$ of $n$-sided polygons in the plane and a query polygon $W$ we give algorithms to find all $Z_\ell$ such that $W=f(Z_\ell)$ with $f$ an unknown similarity transformation in time independent of the size of the collection. If $f$ is a known affine transformation, we show how to find all $Z_\ell$ such that $W=f(Z_\ell)$ in $O(n+\log(m))$ time. For a pair $W,W^\prime$ of polygons we can find all the pairs $Z_\ell,Z_{\ell^\prime}$ such that $W=f(Z_\ell)$ and $W^\prime=f(Z_{\ell^\prime})$ for an unknown affine transformation $f$ in $O(m+n)$ time. For the case of triangles we also give bounds for the problem of matching triangles with variable vertices, which is equivalent to affine matching triangles in noisy conditions.