Name
Abstract | ||
|---|---|---|
Shape recognition, an important portion of image processing, has been widely applied in many research and application areas. Traditional Hough transform, which is a modern shape recognition technique, incurs unbearable execution time and memory storage cost during the extraction of high-dimensional shapes. This paper presents an approach for circle extraction based on generalized image projection and parallelizes it on several brands of GPUs. Experiments shows that GPUs can achieve up to almost 500 times speedup with this method over single threaded CPUs, while traditional Hough transform can only achieve about 100 times speedup. Massive parallelization capability and broad memory bandwidth make GPUs feasible for practical use. Combined with some efficient image scaling algorithms, real-time processing of circle extraction can be achieved. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CIT.2011.33 | CIT |
Keywords | Field | DocType |
traditional hough,high-dimensional shape,times speedup,accelerating circle detection,generalized image projection,circle extraction,generalized projection method,memory storage cost,image processing,efficient image,modern shape recognition technique,broad memory,instruction sets,projection method,shape,real time processing,computer architecture,image reconstruction,radiation detector,memory bandwidth,radiation detectors,coprocessors,hough transform | Memory bandwidth,Computer science,CUDA,Image processing,Real-time computing,Artificial intelligence,Coprocessor,Speedup,Computer vision,Parallel computing,Hough transform,Graphics processing unit,Image scaling | Conference |
Citations | PageRank | References |
2 | 0.39 | 6 |
Authors | ||
2 | ||