A skeleton algorithm on clusters for image edge detection

Xiangjian He, T. Hintz, Qiang Wu

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

Abstract

Image edge detection in computer vision and image processing is a process which detects one kind of significant feature in an image that appears as large delta values in intensities. In this paper, a parallel algorithmic skeleton for edge detection is proposed based on the Spiral Architecture and the Gaussian multi-scale theory. UNIX-based network programming mechanisms in C are used for the implementation on a cluster of Sun-workstations. Our work provides an efficient algorithm for edge detection and is robust to noise.

Original languageEnglish
Title of host publicationProceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1359-1364
Number of pages6
ISBN (Electronic)0769509908, 9780769509907
DOIs
Publication statusPublished - 2001
Externally publishedYes
Event15th International Parallel and Distributed Processing Symposium, IPDPS 2001 - San Francisco, United States
Duration: 23 Apr 200127 Apr 2001

Publication series

NameProceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001

Conference

Conference15th International Parallel and Distributed Processing Symposium, IPDPS 2001
Country/TerritoryUnited States
CitySan Francisco
Period23/04/0127/04/01

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications

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