Euro-Par 2004: Euro-Par 2004 Parallel Processing pp 752-759 | Cite as
Towards User Transparent Data and Task Parallel Image and Video Processing: An Overview of the Parallel-Horus Project
Abstract
In the research area of image and video processing, the Horus library [5] has become a valuable system for software driven rapid prototyping, and an essential vehicle for knowledge transfer at the level of universities and expertise centers. Due to its strictly sequential implementation, however, Horus can not always satisfy all demands for high performance. As computational requirements for the processing of large image sets and video streams continue to increase, it is essential to provide a Horus implementation that applies to high performance computers.
As researchers in image and video processing can not be expected to also become experts in parallel computing, the Parallel-Horus project aims to shield Horus users from all intrinsic complexities of parallelization. This paper presents an overview of the Parallel-Horus project; it discusses the project’s goals, as well as current and future research directions. Also, the efficiency of the current Parallel-Horus implementation is demonstrated by evaluating a strictly sequential state-of-the-art imaging application.
Keywords
Video Stream Software Architecture Parallel Image Document Image Video ProcessingPreview
Unable to display preview. Download preview PDF.
References
- 1.Bagdanov, A.D., et al.: Multi-scale Document Description using Rectangular Granulometries. In: Document Analysis Systems V, August 2002, pp. 445–456 (2002)Google Scholar
- 2.Bal, H.E., et al.: The Distributed ASCI Supercomputer Project. Operating Systems Review 34(4), 76–96 (2000)CrossRefGoogle Scholar
- 3.Jamieson, L.H., et al.: A Software Environment for Parallel Computer Vision. IEEE Computer 25(2), 73–75 (1992)Google Scholar
- 4.Juhasz, Z., et al.: A PVM Implementation of a Portable Parallel Image Processing Library. In: Ludwig, T., Sunderam, V.S., Bode, A., Dongarra, J. (eds.) PVM/MPI 1996 and EuroPVM 1996. LNCS, vol. 1156, pp. 188–196. Springer, Heidelberg (1996)Google Scholar
- 5.Koelma, D., et al.: Horus C++ Reference, Version 1.1. Technical report, ISIS, Faculty of Science, University of Amsterdam, The Netherlands (January 2002)Google Scholar
- 6.Lee, C., Hamdi, M.: Parallel Image Processing Applications on a Network of Workstations. Parallel Computing 21(1), 137–160 (1995)MATHCrossRefGoogle Scholar
- 7.Morrow, P.J., et al.: Efficient Implementation of a Portable Parallel Programming Model for Image Processing. Concurrency: Pract. & Exp. 11, 671–685 (1999)CrossRefGoogle Scholar
- 8.Nicolescu, C., Jonker, P.: A Data and Task Parallel Image Processing Environment. Parallel Computing 28(7-8), 945–965 (2002)MATHCrossRefGoogle Scholar
- 9.Oliveira, P., du Buf, H.: SPMD Image Processing on Beowulf Clusters: Directives and Libraries. In: Proc. IPDPS 2003, Nice, France (April 2003)Google Scholar
- 10.van Osta, P., et al.: The Principles of Scale Space Applied to Structure and Colour in Light Microscopy. Proc. Royal Microscop. Soc. 37(3), 161–166 (2002)Google Scholar
- 11.Pancake, C.M., Bergmark, D.: Do Parallel Languages Respond to the Needs of Scientific Programmers? IEEE Computer 23(12), 13–23 (1990)Google Scholar
- 12.Ritter, G.X., Wilson, J.N.: Handbook of Computer Vision Algorithms in Image Algebra. CRC Press, Inc., Boca Raton (1996)MATHGoogle Scholar
- 13.Seinstra, F.J., Koelma, D.: P-3PC: A Point-to-Point Communication Model for Automatic and Optimal Decomposition of Regular Domain Problems. IEEE Transactions on Parallel and Distributed Systems 13(7), 758–768 (2002)CrossRefGoogle Scholar
- 14.Seinstra, F.J., Koelma, D.: User Transparency: A Fully Sequential Programming Model for Efficient Data Parallel Image Processing. Concurrency and Computation: Practice and Experience 16(6), 611–644 (2004)CrossRefGoogle Scholar
- 15.Seinstra, F.J., Koelma, D., Bagdanov, A.D.: Finite State Machine Based Optimization of Data Parallel Regular Domain Problems Applied in Low Level Image Processing. IEEE Transactions on Parallel and Distributed Systems (2004) (in press)Google Scholar
- 16.Seinstra, F.J., Koelma, D., Geusebroek, J.M.: A Software Architecture for User Transparent Parallel Image Processing. Parallel Computing 28(7-8), 967–993 (2002)MATHCrossRefGoogle Scholar
- 17.Snoek, C.G.M., Worring, M.: Multimodal Video Indexing: A Review of the State-of-the-art. Multimedia Tools and Applications (2004) (in press)Google Scholar
- 18.Squyres, J.M., et al.: Cluster-Based Parallel Image Processing. Technical report, Lab. for Scientific Computing, Univ. Notre Dame, Indiana, USA, TR 96-9 (1996)Google Scholar
- 19.Sterling, T., et al.: BEOWULF: A Parallel Workstation for Scientific Computation. In: Proc. ICPP 1995, Oconomowoc, USA, August 1995, pp. I:11–14 (1995)Google Scholar
- 20.Taniguchi, R., et al.: Software Platform for Parallel Image Processing and Computer Vision. In: Proc. SPIE, San Diego, USA, July 1997, vol. 3166, pp. 2–10 (1997)Google Scholar
- 21.Unger, S.H.: A Computer Oriented towards Spatial Problems. Proceedings of the Institute of Radio Engineers 46, 1744–1750 (1958)Google Scholar
- 22.Vendrig, J.: Interactive Exploration of Visual Content. PhD thesis, ISIS, Faculty of Science, University of Amsterdam, The Netherlands (October 2002)Google Scholar
- 23.Webb, A.G.: Introduction to Biomedical Imaging. Wiley-IEEE Press (2002)Google Scholar