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Parallelizing and Optimizing LIP-Canny Using NVIDIA CUDA

  • Rafael Palomar
  • José M. Palomares
  • José M. Castillo
  • Joaquín Olivares
  • Juan Gómez-Luna
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6098)

Abstract

The Canny algorithm is a well known edge detector that is widely used in the previous processing stages in several algorithms related to computer vision. An alternative, the LIP-Canny algorithm, is based on a robust mathematical model closer to the human vision system, obtaining better results in terms of edge detection. In this work we describe LIP-Canny algorithm under the perspective from its parallelization and optimization by using the NVIDIA CUDA framework. Furthermore, we present comparative results between an implementation of this algorithm using NVIDIA CUDA and the analogue using a C/C++ approach.

Keywords

Shared Memory Global Memory Traditional Operator General Purpose Graphic Processing Unit Traditional Operator Approach 
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 2010

Authors and Affiliations

  • Rafael Palomar
    • 1
  • José M. Palomares
    • 1
  • José M. Castillo
    • 1
  • Joaquín Olivares
    • 1
  • Juan Gómez-Luna
    • 1
  1. 1.Department of Computer Architecture, Electronics and Electronic Technology Computer Architecture AreaUniversity of Córdoba 

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