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

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>>

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