Real time circle detection using OpenCL accelerated Hough transform

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Uploaded by on Mar 12, 2011

This video is a demonstration of CMSoft's GPU accelerated Hough transform algorithm to be presented as an OpenCLTemplate case study.

In our tests we could detect 37 coins in the acceptable rate of 7 fps (real time circle detection) using the Hough transform. Notice the robustness of the detection.

The image taken from the webcam is preprocessed with a Median filter followed by Sobel edge detection and a thinning algorithm. Then, a Generalized Hough Transform is performed using a custom, user-defined shape.

Soundtrack is a small cut from Trenzinho Caipira.

Visit http://www.cmsoft.com.br for more details.

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Uploader Comments (mcgyver125)

  • Working on a paper about this for next year, I still want to do some fine tuning.

    I have a Radeon 5770. I want to get my hands on a 6xxx series with double-precision capabilities soon though.

  • Is any paper about this?

  • @zouzounis

    Not about the OpenCL acceleration, but you can find many about the Hough transform. We intend to publish an improved version we've been working on in some computer vision next year.

  • In my opinion FPGAs are the future of embedded systems as GPUs are the future of PC-based systems as far as high-performance computing is concerned. A somewhat generic tip would be to locate the bottleneck of the processing and focus on it. This is kind of generic but so is the question... I hope this helps

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  • What gpu do you have?

  • Moeda real? Brasil!?

    Muito legal o trabalho! Estou iniciando um trabalho(começando mesmo!) onde pretendo detectar estruturas circulares em tempo real, por isso estou buscando trabalhos que tenham aplicações semelhantes, mas a transformada de hough não tem me atendido muito bem ;/, e além do mais precisaria rodar num dispositivo móvel, então estou pensando em abandonar a idéia.

    Congratulations buddy!

    Great job!

  • I am doing a similar project with an FPGA... do you reckon I can get real time speeds (a few fps). Any tips?

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