Road / Traffic Sign Recognition

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Uploaded by on Aug 30, 2010

* Road / Traffic Sign Detection and Recognition

1. Normal Environments
2. Illumination Variations
3. Night Environments
4. Road Sign Rotation
5. Multiple Road Signs
6. Maximum Performance

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Uploader Comments (moonhwiLee)

  • great.....what technique are u using?

    template matching?

  • @ankit123ful

    I use color-based methods for ROI extraction.

    NN+SVM is used to recognize road sign.

  • @moonhwiLee

    What does NN+SVM mean? Can you please give a little more details? Thanks!

  • @adyandon

    Please find these algorithm:-)

    NN : Neural Network

    SVM : Support Vector Machine

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All Comments (18)

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  • Are you doing traffic sign detection or recognition?because your system does not specify the type of road sign,it just detect and show it.

  • What do you think is taking more juice from the cpu? finding the signs in those high resolution images? or doing the image recognition?

    I see that you are using a pretty powerful cpu for this (3Ghz quad).

    I find it amazing that small digital cameras nowadays run super fast detection of multiple faces, but I doubt they use such a powerful cpu as you are using. I wonder how they manage to do that. Using a specialized processor, like a DSP I guess?

  • Which technical language have you used to implement this project: C, Visual C++ or Matlab?

  • Hi Which camera did you choose?

  • Hi Amazing work!!

    Which camera you used ?

  • Hi moonhwiLee!

    Can you give me any hint about how you defined the Noise class? For example in one case scenario I used about 2500 normalized images of the 30 speed limit sign and about 1800 images labeled as Noise. In training/testing the SVM classifier I got over 90% accuracy but when testing on real video, almost everything gets labeled as Noise.

    Thanks in advance!

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