Summary: Parallel Marker Based Image
Segmentation with Watershed
Alina N. Moga
AlbertLudwigsUniversit¨at, Institute for Informatics
Universit¨at Gel¨ande Flugplatz, Geb. 052, D79085 Freiburg i.Br., Germany
Signal Processing Laboratory, Tampere University of Technology
P.O. Box 553, FIN33101 Tampere, Finland
Published in Journal of Parallel and Distributed Computing
1 This research has been supported by the Graduate School in Electronics, Telecommunication
and Automation (GETA), Finland, and the Edinburgh Parallel Computing Centre in the Training
and Research on Advanced Computing Systems (TRACS) program.
Parallel Marker Based Watershed
Abstract. The parallel watershed transformation used in grayscale image segmentation
is here augmented to perform with the aid of a priori supplied image cues, called markers.
The reason for introducing markers is to calibrate a resilient algorithm to oversegmenta
tion. In a hybrid fashion, pixels are first clustered based on spatial proximity and graylevel