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Stream-Based Data Filtering for Accelerating Metrological Data Characterization

Su, Yang, Xu, Zhijie and Jiang, Xiang (2008) Stream-Based Data Filtering for Accelerating Metrological Data Characterization. In: Proceedings of the 14th International Conference on Automation and Computing. ICAC, pp. 81-85. ISBN 978-0-9555294-2-0

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      Abstract

      The main task of engineering surface metrology is to characterize a surface by assessing components such as form, waviness and roughness that correspond to different wavelength segments in the frequency domain, which are often extracted by deploying filtering techniques. The effectiveness of a specific kind of filtering algorithms is jointly determined by their filtering accuracy and computational efficiency. In this paper, a data stream-based programming paradigm is introduced which takes advantage of the programmability and parallel computation capacity of modern graphics process unit (GPU) to execute and accelerate the Gaussian filtering process that is extensively used in surface metrological data processing. In contrast to the results obtained by running MATLAB simulation kit for similar processes, the software framework speeds up the filtering process substantially while yielding satisfying accuracy as that of the corresponding MATLAB program, which proved the practicability and validity of the proposed computation model.

      Item Type: Book Chapter
      Additional Information: Paper presented at the 14th International Conference on Automation and Computing (ICAC 2008 Conference), 6 September 2008, Brunel University
      Uncontrolled Keywords: Surface metrology, Graphics process unit, Gaussian filtering, Parallel computation
      Subjects: T Technology > T Technology (General)
      Schools: School of Computing and Engineering
      School of Computing and Engineering > Centre for Precision Technologies
      School of Computing and Engineering > Centre for Precision Technologies > Surface Metrology Group
      School of Computing and Engineering > Computer Graphics, Imaging and Vision Research Group
      Related URLs:
      Depositing User: Yuanping Xu
      Date Deposited: 22 Jun 2009 12:21
      Last Modified: 05 Jan 2011 13:17
      URI: http://eprints.hud.ac.uk/id/eprint/4744

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