Systolic preprocessor for online morphologic operations

Olivier Deforges; Nicolas Normand

doi:10.1117/12.279619

19 September 1997 Systolic preprocessor for online morphologic operations

Olivier Deforges, Nicolas Normand

Proceedings Volume 3166, Parallel and Distributed Methods for Image Processing; (1997) https://doi.org/10.1117/12.279619
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

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.

Citation Download Citation

Olivier Deforges and Nicolas Normand "Systolic preprocessor for online morphologic operations", Proc. SPIE 3166, Parallel and Distributed Methods for Image Processing, (19 September 1997); https://doi.org/10.1117/12.279619

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