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.
This work was supported by the Junta de Andalucía (Projects PR06-TIC-02109 and PR07-TIC-02800), and the Ministry of Education of Spain (Project TIC2003-06623).
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Ujaldón, M., Guil, N. (2009). High Performance Circle Detection through a GPU Rasterization Approach. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_36
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DOI: https://doi.org/10.1007/978-3-642-02172-5_36
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