Summary: Parallel Marker Based Image
Segmentation with Watershed
Transformation
Alina N. Moga
Albert­Ludwigs­Universit¨at, Institute for Informatics
Universit¨at Gel¨ande Flugplatz, Geb. 052, D­79085 Freiburg i.Br., Germany
Moncef Gabbouj
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
Transformation
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

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

Collections: Computer Technologies and Information Sciences