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Constan t-Time Hough Transform On A 3D Reconfigurable Mesh Using Fewer Processors

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1800)

Abstract

The Hough transform has many applications in image processing and computer vision, including line detection, shape recognition and range alignment for moving imaging objects. Many constant-time algorithms for computing the Hough transform have been proposed on reconfigurable meshes [1, 5, 6, 7, 9, 10]. Among them, the ones described in [1, 10] are the most efficient. For a problem with an N × N image and an n × n parameter space, the algorithm in [1] runs in a constant time on a 3D nN × N × N reconfigurable mesh, and the algorithm in [10] runs in a constant time on a 3D n2 × N × N reconfigurable mesh. In this paper, a more efficient Hough transform algorithm on a 3D reconfigurable mesh is proposed. For the same problem, our algorithm runs in constant time on a 3D n log2N × N × N reconfigurable mesh.

Keywords

Black Pixel Hough Transform Shape Recognition Switch Setting Local Switch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Yi Pan
    • 1
  1. 1.Department of Computer ScienceUniversity of DaytonDaytonUSA

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