Reconfigurable mesh algorithms for image shrinking, expanding, clustering, and template matching

Abstract

Parallel reconfigurable mesh algorithms are developed for the following image processing problems: shrinking, expanding, clustering, and template matching. The authors' N*N reconfigurable mesh algorithm for the q-step shrinking and expansion of a binary image takes O(1) time. One pass of the clustering algorithm for N patterns and K centers can be done in O(MK+KlogN), O(KlogNM), and O(M+logNMK) time using N, NM, and NMK processors, respectively. For template matching using an M*M template and an N*N image, the authors' algorithms run in O(M/sup 2/) time when N/sup 2/ processors are available and in O(M) time when N/sup 2/M/sup 2/ processors are available.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>