The distributed ASCI Supercomputer project
ACM SIGOPS Operating Systems Review
A Minimum Cost Approach for Segmenting Networks of Lines
International Journal of Computer Vision
Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Lazy Programmer's Approach to Building a Parallel Image processing Library
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
EASY PIPE: An ``EASY to use'' Parallel Image processing Environment based on algorithmic skelekons
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
A Software Architecture for User Transparent Parallel Image Processing on MIMD Computers
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Object-Oriented Parallel Image Processing Library
PaCT '09 Proceedings of the 10th International Conference on Parallel Computing Technologies
A parallel solution for high resolution histological image analysis
Computer Methods and Programs in Biomedicine
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Although many image processing applications are ideally suited for parallel implementation, most researchers in imaging do not benefit from high performance computing on a daily basis. Essentially, this is due to the fact that no parallelization tools exist that truly match the image processing researcher's frame of reference. As it is unrealistic to expect imaging researchers to become experts in parallel computing, tools must be provided to allow them to develop high performance applications in a highly familiar manner.In an attempt to provide such a tool, we have designed a software architecture that allows transparent (i.e., sequential) implementation of data parallel imaging applications for execution on homogeneous distributed memory MIMD-style multicomputers. This paper gives an assessment of the architecture's effectiveness in providing significant performance gains. In particular, we describe the implementation and automatic parallelization of three well-known example applications that contain many fundamental imaging operations: (1) template matching, (2) multi-baseline stereo vision, and (3) line detection. Based on experimental results we conclude that our architecture constitutes a powerful and user-friendly tool for obtaining high performance in many important image processing research areas.