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(M²) time when N² processors are available and in O(M ) time when N²M² processors are available