Summary: A PARALLEL GENETIC ALGORITHM FOR OPTIMIZING MORPHOLOGI­
CAL FILTERS ON INHOMOGENEOUS WORKSTATION CLUSTERS
Proceedings of the Fourth International Workshop on Parallel Image Analysis (IWPIA'95), S.
Miguet and A. Montanvert 1995, eds., LIP­ENS, Lyon, France, Dec. 1995, 171­182
P Kraft, M N¨olle \Lambda , G Schreiber \Lambda , S Marshall, H Burkhardt \Lambda
University of Strathclyde, Glasgow, Scotland
\Lambda Technische Universit¨at Hamburg­Harburg, Hamburg, Germany
ABSTRACT
In this paper a modification of a standard parallel ge­
netic algorithm (SPGA) is introduced which can be
run efficiently on different types of parallel comput­
ers. The purpose of the algorithm is to find optimal
morphological filters for grey scale image processing
tasks. The structure of the developed General Par­
allel Genetic Algorithm (GPGA) is based on a new
subpopulation model which uses an integral load bal­
ancing and soft synchronization mechanism. It is de­
signed to lead to good parallelization efficiencies even
on distributed workstation clusters with multi­user
operating systems. This is especially important for

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

Collections: Computer Technologies and Information Sciences