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Proceedings Paper

Accelerating sub-pixel marker segmentation using GPU
Author(s): Holger Handel
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Paper Abstract

Sub-pixel accurate marker segmentation is an important task for many computer vision systems. The 3D-positions of markers are used in control loops to determine the position of machine tools or robot end-effectors. Accurate segmentation of the marker position in the image plane is crucial for accurate reconstruction. Many subpixel segmentation algorithms are computationally intensive, especially when the number of markers increases. Modern graphics hardware with its massively parallel architecture provides a powerful tool for many image segmentation tasks. Especially, the time consuming sub-pixel refinement steps in marker segmentation can benefit from the recent progress. This article presents an implementation of a sub-pixel marker segmentation framework using the GPU to accelerate the processing time. The image segmentation chain consists of two stages. The first is a pre-processing stage which segments the initial position of the marker with pixel accuracy, the second stage refines the initial marker position to sub-pixel accuracy. Both stages are implemented as shader programs on the GPU. The flexible architecture allows it to combine different pre-processing and sub-pixel refinement algorithms. Experimental results show that significant speed-up can be achieved compared to CPU implementations, especially when the number of markers increases.

Paper Details

Date Published: 5 February 2009
PDF: 11 pages
Proc. SPIE 7244, Real-Time Image and Video Processing 2009, 72440K (5 February 2009); doi: 10.1117/12.806160
Show Author Affiliations
Holger Handel, Univ. of Heidelberg (Germany)


Published in SPIE Proceedings Vol. 7244:
Real-Time Image and Video Processing 2009
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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