A Euclidean distance transform in linear time
نویسنده
چکیده
A new linear time scanning algorithm for the exact Euclidean distance transform is presented. It is shorter and uses a smaller data structure than the approximating algorithms of Danielsson. The algorithm consists of two phases. The rst phase uses two scans per line to compute the distance transform over the columns of the image. Then the second phase uses two scans per row. Informally speaking, each of these row scans uses the intersections of the remainder of the row with the Voronoi cells of the source restricted to the halfplane in the past of the scan point. Since it only uses knowledge accumulated per scan line, the algorithm is well suited for parallellization.
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