Abstract
This paper proposes a parallel algorithm for contour tracking of binary pictures. Given an object contour composed by O(N) pixels, our algorithm computes in constant time the next layer of the contour of that object, using the weakest parallel model, i.e. an Exclusive Read Exclusive Write (EREW) Parallel Random Access Machine (PRAM). As an application of the technique we show a work-optimal parallel thinning algorithm for binary pictures, based on Pavlidis' characterization of a skeleton. Our algorithm improves on previous solutions by producing a list of coordinates corresponding to the skeleton contour in O(N) time with O(N) processors in an EREW PRAM, where N is the width of the picture.
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