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

John Jenq, Sartaj Sahni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

37 Scopus citations

Abstract

Parallel reconfigurable mesh algorithms are developed for the following image processing problems: shrinking, expanding, clustering, and template matching. Our N×N reconfigurable mesh algorithm for the q-step shrinking and expansion of a binary image takes 0 (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, our algorithms run in O (M2) time when N2 processors ate available and in O (M) time when N2M2 processors are available.

Original languageEnglish
Title of host publicationProceedings - 5th International Parallel Processing Symposium, IPPS 1991
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages208-215
Number of pages8
ISBN (Electronic)0818691670, 9780818691676
DOIs
StatePublished - 1 Jan 1991
Event5th International Parallel Processing Symposium, IPPS 1991 - Anaheim, United States
Duration: 30 Apr 19912 May 1991

Publication series

NameProceedings - 5th International Parallel Processing Symposium, IPPS 1991

Conference

Conference5th International Parallel Processing Symposium, IPPS 1991
CountryUnited States
CityAnaheim
Period30/04/912/05/91

Keywords

  • Clustering
  • Expanding
  • Image processing
  • Parallel algorithms
  • Reconfigurable mesh computer
  • Shrinking
  • Template matching

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