NPAC Technical Report SCCS-596
A Data Parallel Algorithm for Solving the Region Growing Problem on the Connection Machine
Nawal Copty, Sanjay Ranka, Geoffrey Fox, Ravi Shankar
Submitted January 1 1994
Abstract
Region growing is a general technique for image segmentation, where
image characteristics are used to group adjacent pixels together to
form regions. This paper presents a parallel algorithm for solving
the region growing problem based on the split and merge approach, and
uses it to test and compare various parallel architectures and
programming models. The implementations were done on the Connection
Machine, models CM-2 and CM-5, in the data parallel and message
passing programming models. Randomization was introduced in breaking
ties during merging to increase the degree of parallelism, and only
one and two-dimensional arrays of data were used in the
implementations.