Parallel Algorithms for Image Enhancement and Segmentation by Region Growing with an Experimental Study

This paper presents e cient and portable implementations of a useful image enhancement process, the Symmetric Neighborhood Filter SNF, and an image segmentation technique which makes use of the SNF and a variant of the conventional connected components algorithm which we call -Connected Components. Our general framework is a single-address space, distributed memory programming model. We use e cient techniques for distributing and coalescing data as well as e cient combinations of task and data parallelism. The image segmentation algorithm makes use of an e cient connected components algorithm which uses a novel approach for parallel merging. The algorithms have been coded in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2, Cray Research T3D, Meiko Scienti c CS-2, Intel Paragon, and workstation clusters. Our experimental results are consistent with the theoretical analysis and provide the best known execution times for segmentation, ev...

• Type: Conference
• Year: 1996
• Where: IPPS
• Authors: David A. Bader, Joseph JáJá, David Harwood, Larry S. Davis
• Keywords: Connected Components, Distributed And Parallel Computing, Image Segmentation, Image Segmentation Technique, IPPS 1996