Multiplatform GPGPU Implementation of the Active Contours Without Edges Algorithm

Abstract

An OpenCL implementation of the Active Contours Without Edges algorithm is presented. The proposed algorithm uses the General Purpose Computing on Graphics Processing Units (GPGPU) to accelerate the original model by parallelizing the two main steps of the segmentation process, the computation of the Signed Distance Function (SDF) and the evolution of the segmented curve. The proposed scheme for the computation of the SDF is based on the iterative construction of partial Voronoi diagrams of a reduced dimension and obtains the exact Euclidean distance in a time of order O(N/p), where N is the number of pixels and p the number of processors. With high resolution images the segmentation algorithm runs 10 times faster than its equivalent sequential implementation. This work is being done as an open source software that, being programmed in OpenCL, can be used in different platforms allowing a broad number of final users and can be applied in different areas of computer vision, like medical imaging, tracking, robotics, etc. This work uses OpenGL to visualize the algorithm results in real time.

Cite

@inproceedings{zavalaromero2012multiplatform,
  title = {Multiplatform GPGPU Implementation of the Active Contours Without Edges Algorithm},
  author = {Zavala-Romero, Olmo and Meyer-Baese, Anke and Meyer-Baese, Uwe},
  year = {2012},
  url = {/media/papers/Proceedings/2012 - Zavala-Romero et al. - Multiplatform GPGPU Implementation of the Active Contours Without Edges Algorithm_proceedings.pdf},
}

Topics

• Computer Vision
• Health
• SciVis