Share Email Print

Proceedings Paper

An Investigation Into Intermediate-Level Image Processing Using A Tree-Connected Transputer Network
Author(s): K. W. Chow; A. J. McCollum; B. G. Batchelor
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The regularity and local neighbourhood interdependence of picture data and the repetitive nature of many feature extraction algorithms may be usefully exploited in the design of specialised computer architectures for image processing at the pixel level. However, the features detected in the image will vary in type, number, position and size. The irregularity of this feature data prevents it from being easily partitioned. Also, at subsequent "intermediate" processing levels, various feature extraction, grouping and measurement algorithms will be employed. These are often more complex than low-level operations, and may be broken down into concurrently operating sub-processes. A more flexible multiprocessor architecture is therefore required, on to which a variety of algorithms can be mapped. This paper describes an augmented tree-structured MIMD processor network for intermediate level image processing. The Inmos Transputer has been chosen as the basic architectural building block. The programming and operation of the proposed architecture is illustrated using a Hough transform algorithm and a connected region finding routine.

Paper Details

Date Published: 21 March 1989
PDF: 7 pages
Proc. SPIE 1004, Automated Inspection and High-Speed Vision Architectures II, (21 March 1989); doi: 10.1117/12.949004
Show Author Affiliations
K. W. Chow, University of Wales College of Cardiff (United Kingdom)
A. J. McCollum, University of Wales College of Cardiff (United Kingdom)
B. G. Batchelor, University of Wales College of Cardiff (United Kingdom)

Published in SPIE Proceedings Vol. 1004:
Automated Inspection and High-Speed Vision Architectures II
Michael J. W. Chen, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?