Peeling Digital Potatoes
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The potato-peeling problem (also known as convex skull) is a fundamental computational geometry problem and the fastest algorithm to date runs in $O(n^8)$ time for a polygon with $n$ vertices that may have holes. In this paper, we consider a digital version of the problem. A set $K \subset \mathbb{Z}^2$ is digital convex if $conv(K) \cap \mathbb{Z}^2 = K$, where $conv(K)$ denotes the convex hull of $K$. Given a set $S$ of $n$ lattice points, we present polynomial time algorithms to the problems of finding the largest digital convex subset $K$ of $S$ (digital potato-peeling problem) and the largest union of two digital convex subsets of $S$. The two algorithms take roughly $O(n^3)$ and $O(n^9)$ time, respectively. We also show that those algorithms provide an approximation to the continuous versions.
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Peeling Rotten Potatoes for a Faster Approximation of Convex Cover
A new O(log n)-approximation algorithm for minimum convex cover of polygons that runs substantially faster than the prior O(n^29 log n) bound by reducing the problem to maximum-weight paths in visibility DAGs.
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