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. Our NxN 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 0 (M + logNMK) time using N, NM, and NMK processors, respectively. For template matching using an MxM template and an NxN image, our algorithms run in O (M 2) time when N 2 processors are available and in O (M) time when N2M processors are available

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