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Towards Parallel Processing of Multisensed Data

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Part of the book series: NATO ASI Series ((NATO ASI F,volume 83))

Abstract

According to applications, data may come from many different sources even simultaneously as in multisensed environments: this implies fast input channels and, consequently, processing elements able to provide the information required to match the specific domain requests. For instance, in an autonomous vehicle control system the telecameras and other sensors should allow the computer unit of the vehicle to decide and manage the driving strategy of such vehicle.

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References

  1. Ballard, D.H.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition, vol. 3, n. 2, pp. 110–122, 1981.

    Google Scholar 

  2. Bongiovanni, G., Guerra C., Levialdi, S.: Computing the Hough transform on a pyramid computer. Submitted, 1987.

    Google Scholar 

  3. Chuang, H.Y., Li, C.C.: A systolic array for straight line detection by modified Hough transform. In: IEEE Work, on Comp. Architecture for Pattern Analysis and Image Data Base Management, pp. 300–304, 1985.

    Google Scholar 

  4. Cantoni, V., Levialdi, S., edits.: Pyramidal Systems for Computer Vision. Springer-Verlag, Berlin, NATO ARW, Series F, Vol. 25, 1986.

    MATH  Google Scholar 

  5. Chandran, S., Mount, D., Shared memory model and the medial axis transform, In: IEEE Work, on Computer Architectures for Pattern Analysis and Machine Intelligence, pp. 115–121, 1987.

    Google Scholar 

  6. Cinque, L., Guerra, C., Levialdi, S.: The medial axis transform on a pyramid computer. In: Proc. of Int. Conf. on Image Analysis and Processing, Positano, Italy, 1989.

    Google Scholar 

  7. Cypher, R., Sanz, J.L.C.: The Hough transform has O(n) complexity on a SIMD nxn mesh array architecture. In: IEEE Work, on Computer Architectures for Pattern Analysis and Machine Intelligence, pp. 115–121, 1987.

    Google Scholar 

  8. Duda, R.O., Hart, P.E.: Use of the Hough transform to detect lines and curves in pictures. Communie. ACM, vol.15, n. 1, 1972.

    Google Scholar 

  9. Fischer, A. L., Highnam, P. T.: Real-time image processing on scanline array processors. In: IEEE Workshop on Computer Architectures for Pattern Analysis and Machine Intelligence, pp. 484–489, 1985.

    Google Scholar 

  10. Guerra, C. Hambrusch, S.: Parallel algorithms for line detection on a mesh. Journal of Parallel and Distributed Computing, vol. 6, pp. 1–20, Feb. 1989.

    Article  Google Scholar 

  11. Hough, P. V.: Methods and means to recognize complex patterns, U.S. Patent 3,069,654, 1962.

    Google Scholar 

  12. Kung, H.T., Webb, J.: Mapping image processing operations onto a linear systolic machine. Distributed Computing, pp. 246–257, 1986.

    Google Scholar 

  13. Ibrahim, H. A., Kender, J.R., Shaw, D.E.: The analysis and performance of two middle-level vision tasks on a fine-grained SIMD tree machine. In: Proc. of the IEEE. Conf. on Computer Vision and Pattern Recognition, pp. 248–256, 1985.

    Google Scholar 

  14. Hillis, W. D.: the Conncetion Machine. MIT Press, Mass, 1985.

    Google Scholar 

  15. Jolion, J. M., Rosenfeld, A.: An O(logn) pyramid Hough transform. Pattern Recognition Letters, vol. 9, pp. 343–349, 1989.

    Article  MATH  Google Scholar 

  16. Levialdi, S., edit.: Multicomputer Vision. Academic Press, London, 1985.

    Google Scholar 

  17. Li, H., Lavin, M., Le Master, R.: Fast Hough transform: a hierarchical approach. Computer Vision Graphics and Image Processing, vol 36, pp. 139–161, 1986.

    Article  Google Scholar 

  18. Li, H., Maresca, M.: Polymorphic torus: a new architecture for vision computation. In: Proc. of the Work, on Computer Architecture for Pattern Anal, and Mach. Intel., pp.176–184, 1987.

    Google Scholar 

  19. Little, J.J., Blelloch, G. and Cass, T.: How to program the Connection Machine. In: Proc. of the Work, on Computer Architecture for Pattern Anal, and Mach. Intel., pp. 11–19, 1987.

    Google Scholar 

  20. Miller, R., Stout, Q.: Convexity algorithms for pyramid computers. In: Proc. Int. Conf. Parallel Processing, pp. 177–184, 1984.

    Google Scholar 

  21. Miller, R., Stout, Q.: Data movement techniques for the pyramid computer. SIAM J. on Computing, vol. 16, n.1, pp. 38–60, 1987.

    Article  MATH  MathSciNet  Google Scholar 

  22. Mudge, T. N.: Vision algorithms for hypercube machines. In: Proc. Comp. Arch, for Pattern Analysis and Image Database Manag., pp. 225–231, 1985.

    Google Scholar 

  23. Rosenfeld, A., (Ed.): Multiresolution Image Processing and Analysis. Springer-Verlag, 1984.

    MATH  Google Scholar 

  24. Sanz, J.L.C., Dinstein, I.: Projection-based geometrical feature extraction for computer vision: algorithms in pipeline architectures. IEEE Trans, on PAMI, vol.9, n. 1, pp. 160–168, 1987.

    Article  Google Scholar 

  25. Stout, Q.: Hypercubes and pyramids. In: Pyramidal systems for Computer Vision, NATO ASI series, V. Cantoni and S. Levialdi eds., pp. 75–89, 1986.

    Google Scholar 

  26. Tanimoto, S.L.: Programming techniques for hierarchical parallel image processors. In: Multicomputers for image processing, (K. Preston, and L. Uhr eds.), Academic Press, pp. 421–429, 1984.

    Google Scholar 

  27. Tanimoto, S. L., Kingler, A.: Structured Computer Vision. Academic Press., 1980.

    Google Scholar 

  28. Uhr, L.: Layered recognition cone networks that preprocess, classify, and describe. IEEE Trans, on Comp., pp. 758–768, 1972.

    Google Scholar 

  29. Valiant, L. G.: A scheme for parallel communication. SIAM J. on Computing, vol. 11, pp. 350–361, 1982.

    Article  MATH  MathSciNet  Google Scholar 

  30. Wu, A., Bhaskar, S.K., Rosenfeld, AA.: Computation of geometric properties from the medial axis transform in O(nlogn) time. CVIP, vol. 34, pp. 76–92, 1986.

    Google Scholar 

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© 1992 Springer-Verlag Berlin Heidelberg

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Guerra, C., Levialdi, S. (1992). Towards Parallel Processing of Multisensed Data. In: Sood, A.K., Wechsler, H. (eds) Active Perception and Robot Vision. NATO ASI Series, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77225-2_16

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  • DOI: https://doi.org/10.1007/978-3-642-77225-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-77227-6

  • Online ISBN: 978-3-642-77225-2

  • eBook Packages: Springer Book Archive

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