Abstract
GPUs have recently attracted our attention as accelerators for a wide variety of algorithms, including assorted examples within the pattern recognition field. After proving the effectiveness of the GPU for computing the Circle Hough Transform [Ujaldon et al. (2008)], we present in this paper a radius compensation method which improves the accuracy and speed-up using the GPU rasterizer. Experimental results confirm a higher precision in circles detection and up to 27% additional savings in the GPU computational time on a GeForce 8800 GTX for a 1024x1024 sample image, thus enhancing the execution of the Circle Hough Transform on a low-cost and emerging architecture like the GPU.KeywordsEdge PointCircle CenterHough TransformContour PointActual RadiusThese 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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