Summary: PISA---Parallel Image Segmentation
Alina Lindner (Moga), Andreas Bieniek, and Hans Burkhardt
Institut f¨ur Informatik, Am Flughafen 17, D79110 Freiburg
Abstract. Parallelisation of the watershed segmentation method is studied in this
paper. Starting with a successful parallel watershed design solution, extensive tests
on various parallel machines are presented to prove its portability and performance.
Next, the watershed algorithm has been reformulated as a modified connected
component problem. Consequently, we present a scalable parallel implementation
of the connected component problem, which is the key for the future improving of
the parallel design for the watershed algorithm.
Segmentation is a process of partitioning an image into disjoint regions such that
each region is homogeneous, according to a certain uniformity criterion, and no
union of any two adjacent regions is homogeneous. The problem has been broadly
investigated by scientists using both classical and fuzzy based reasoning techniques.
Different algorithms can be found in the literature seeking for either feature homo
geneity (region growing) or to detect dissimilarities (edge detection) [12,15,23].
Segmentation plays a crucial role in image processing, in particular for coding,