Traffic sign detection and recognition using fuzzy segmentation approach and artificial neural network classifier respectively

@article{Abedin2017TrafficSD,
  title={Traffic sign detection and recognition using fuzzy segmentation approach and artificial neural network classifier respectively},
  author={Zainal Abedin and Prashengit Dhar and Muhammad Kamal Hossenand and Kaushik Deb},
  journal={2017 International Conference on Electrical, Computer and Communication Engineering (ECCE)},
  year={2017},
  pages={518-523}
}
  • Zainal Abedin, Prashengit Dhar, +1 author Kaushik Deb
  • Published in
    International Conference on…
    2017
  • Computer Science
  • Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system where detection of traffic sign is carried out using fuzzy rules based color segmentation method and recognition is accomplished using Speeded Up Robust Features(SURF) descriptor, trained by artificial neural network (ANN) classifier. In the detection step, the region… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 16 REFERENCES

    Traffic Sign Detection and Pattern Recognition Using Support Vector Machine

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    Hsieh,”Boosted road sign detection and recognition

    • Sin-Yu Chen, Jun-Wei
    • In Proc. of Intl. Conference on Machine Learning and Cybernetics,
    • 2008
    VIEW 2 EXCERPTS
    HIGHLY INFLUENTIAL

    Road-Sign Detection and Recognition Based on Support Vector Machines

    VIEW 2 EXCERPTS
    HIGHLY INFLUENTIAL

    Recognizing Text-Based Traffic Signs

    VIEW 1 EXCERPT

    Road Sign Detection Based on YCbCr color model and DtBs Vector

    • Soumenn Chakraborty, Kaushik Deb, ”Bangladeshi
    • 1st international Conference on Computer and Information Engineering,
    • 2015
    VIEW 3 EXCERPTS

    Robust traffic sign recognition with feature extraction and k-NN classification methods

    VIEW 1 EXCERPT