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Proceedings Paper

Systolic preprocessor for online morphologic operations
Author(s): Olivier Deforges; Nicolas Normand
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Paper Abstract

Mathematical morphology is a powerful and widespread tool for image analysis and coding. But for large analysis neighborhoods, it becomes rapidly time consuming on general purpose machines. Many works have been done to decrease the overall complexity by splitting heavy computation tasks into several more efficient ones. Even if significant speedup factors have been achieved using dedicated architectures, the major drawback is that the number of operations required is still dependent on the considered neighborhood size. This paper deals with a systolic network for real time morphological processing since it is able to perform erosions, dilations, openings, and closings during a unique image scan. It implements a new method called 'casual recursive erosion' based on the decomposition of neighborhoods by both dilations and union sets. The resulting architecture presents a low complexity and offers a constant computation time. Reconfigurration of the application only consists in modifying a few array contents. System synthesis onto one FPGA yields very high processing rates.

Paper Details

Date Published: 19 September 1997
PDF: 12 pages
Proc. SPIE 3166, Parallel and Distributed Methods for Image Processing, (19 September 1997); doi: 10.1117/12.279619
Show Author Affiliations
Olivier Deforges, Institut National des Sciences Appliquees de Rennes (France)
Nicolas Normand, IRESTE (France)

Published in SPIE Proceedings Vol. 3166:
Parallel and Distributed Methods for Image Processing
Hongchi Shi; Patrick C. Coffield, Editor(s)

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