Scalable and efficient parallel algorithms for Euclidean distance transform on the LARPBS model

Abstract

A parallel algorithm for Euclidean distance transform (EDT) on linear array with reconfigurable pipeline bus system (LARPBS) is presented. For an image with n/spl times/n pixels, the algorithm can complete EDT transform in O(n log n/c(n) log d(n)) time using n/spl middot/d(n)/spl middot/c(n) processors, where c(n) and d(n) are parameters satisfying 1/spl les/c(n)/spl les/n, and 1<d(n)/spl les/n, respectively. By selecting different c(n) and d(n), the time complexity and the number of processors used can be adjusted. This makes the algorithm highly scalable and flexible. The algorithm also provides a general framework for EDT algorithms on LARPBS, and many existing and unknown parallel EDT algorithms can be deduced from this framework. In particular, if we let c(n)=n, d(n)=n/sup /spl epsiv//, the algorithm can be completed in O(1) time using n/sup 2+/spl epsiv// processors. To the best of our knowledge, this is the most efficient constant-time EDT algorithm on LARPBS.