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Fast Hough Transform on GPUs: Exploration of Algorithm Trade-Offs

  • Gert-Jan van den Braak
  • Cedric Nugteren
  • Bart Mesman
  • Henk Corporaal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)

Abstract

The Hough transform is a commonly used algorithm to detect lines and other features in images. It is robust to noise and occlusion, but has a large computational cost. This paper introduces two new implementations of the Hough transform for lines on a GPU. One focuses on minimizing processing time, while the other has an input-data independent processing time. Our results show that optimizing the GPU code for speed can achieve a speed-up over naive GPU code of about 10×. The implementation which focuses on processing speed is the faster one for most images, but the implementation which achieves a constant processing time is quicker for about 20% of the images.

Keywords

Input Image Augmented Reality Shared Memory Global Memory Edge Pixel 
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 2011

Authors and Affiliations

  • Gert-Jan van den Braak
    • 1
  • Cedric Nugteren
    • 1
  • Bart Mesman
    • 1
  • Henk Corporaal
    • 1
  1. 1.Dept. of Electrical Engineering, Electronic Systems GroupEindhoven University of TechnologyThe Netherlands

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