Fast and scalable algorithms for the euclidean distance transform on the LARPBS

The Euclidean distance transform (EDT) is an operation to convert a binary image consisting of black and white pixels to a representation where each pixel has the Euclidean distance of the nearest black pixel. The EDT has many applications in computer vision and image processing. In this paper, we present an algorithm for computing the EDT of a binary image on the Linear Array with a Reconfigurable Pipelined Bus System (LARPBS), a recently proposed architecture based on optical buses. Our algorithm is deterministic and runs in time for a binary image on an LARPBS with processors, for any fixed , . We also show that our algorithm is highly scalable. If the LARPBS has only processors for , our algorithm runs in time. The algorithm

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