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4 February 2009 Accelerating sub-pixel marker segmentation using GPU
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Holger Handel "Accelerating sub-pixel marker segmentation using GPU", Proc. SPIE 7244, Real-Time Image and Video Processing 2009, 72440K (4 February 2009); doi: 10.1117/12.806160; https://doi.org/10.1117/12.806160
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