Abstract
Uniform image partitioning has been achieved on Spiral Architecture, which plays an important role in parallel image processing on many aspects such as uniform data partitioning, load balancing, zero data exchange between the processing nodes et al. However, when the number of partitions is not the power of seven like 49, each sub-image except one is split into a few fragments which are mixed together. We could not tell which fragments belong to which sub-image. It is an unacceptable flaw to parallel image processing. This paper proposes a method to resolve the problem mentioned above. From the experimental results, it is shown that the proposed method correctly identifies the fragments belonging to the same sub-image and successfully collects them together to be a complete sub-image. Then, these sub-images can be distributed into the different processing nodes for further processing.
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References
Pitas, I.: Parallel Algorithm for Digital Image Processing. Computer Vision and Neural Network, John Wiley & Sons, Chichester, England (1993)
Squyres, J.M., Lumsdaine, A., Stevenson, R.L.: A Cluster-based Parallel Image Processing Toolkit. Proceedins of the IS&T Conference on Image and Video Processing, (San Joes, CA, 1995) 228–239
You, J., Zhu, W.P., Cohen, H.A., Pissaloux, E.: Fast Object Recognition by Parallel Image Matching on a Distributed System. Proceedings of the 17th IEEE Symposium on Parallel and Distributed Processing (1995) 78–85
Koelbel, C.H., Loveman, D.B., Schreiber, R.S., Jr., G.L. S., Zosel, M.E.: The High Performance Fortran Handbook. MIT Press, Cambridge, MA. (1994)
Oberhuber, M.: Distributed High-Performance Image Processing on the Internet. PhD Thesis, Graz University of Technology, Austria (1998)
Sheridan, P., Hintz, T., Moore, W.: Spiral Architecture in Machine Vision. Proceedings of the Australian Occam and Transputer Conference (1991)
Schwartz, E.: Computational Anatomy and Functional Architecture of Striate Cortex: A Spatial Mapping Approach to Perceptual Coding. Vision Research 20 (1980) 645–669
Wu, Q., He, X., Hintz, T.: Distributed Image Processing on Spiral Architecture. Proceedings of the 5th International Conference on Algorithm and Architectures for Parallel Processing, (Beijing, China, 2002) 84–91
Sheridan, P., Hintz, T., Alexander, D.: Pseudo-invariant Image Transformations on a Hexagonal Lattice. Image and Vision Computing, 18(11)(2000). 907–917
Spiral Architecture for Machine Vision. PhD Thesis, University of Technology, Sydney (1996)
He, X., Hintz, T., Szewcow, U.: Affine Integral Invariants and Object Recognition. Proceedings of the High Performance Computing Conference, (Singapore, 1998), 419–423
Wu, Q., He, X., Hintz, T.: Image Rotation without Scaling on Spiral Architecture. Journal of WSCG, 10(2)(2002) 515–520
Bharadwaj, V., Li., X., Ko, C.C.: Efficient Partitioning and Scheduling of Computer Vision and Image Processing Data on Bus Networks Using Divisible Load Analysis. Image and Vision Computing, 18 (2000). 919–938
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Wu, Q., He, X., Hintz, T., Ye, Y. (2003). Complete Image Partitioning on Spiral Architecture. In: Guo, M., Yang, L.T. (eds) Parallel and Distributed Processing and Applications. ISPA 2003. Lecture Notes in Computer Science, vol 2745. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-37619-4_31
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DOI: https://doi.org/10.1007/3-540-37619-4_31
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