Abstract : Considering the requirement of high accuracy and robustness for
traffic sign detection in real-world environments, this paper proposed a
novel method for automatic detection of traffic sign. There are three
main stages in the proposed algorithm:1)segmentation by adaptive
threshold in HSI color space to find the region of interest; 2)eliminate
the noise present in the binary image and the small objects with
morphological operations and mean filter;3)contour extraction and curve
fitting for a better contour by the least square method. Experimental
results show a high success rate and demonstrate that the proposed
framework is invariant to illumination, deformation, and partial
occlusions.
Daoliang Li; Yingyi Chen. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-419 (Part I), pp.263-268, 2014, Computer and Computing Technologies in Agriculture VII. 〈10.1007/978-3-642-54344-9_32〉
https://hal.inria.fr/hal-01220927
Contributeur : Hal Ifip
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Soumis le : mardi 27 octobre 2015 - 10:11:30
Dernière modification le : mercredi 17 janvier 2018 - 10:43:35
Document(s) archivé(s) le : jeudi 28 janvier 2016 - 10:35:32
Bo Peng, Juan Wu. A Novel Robust Method for Automatic Detection of Traffic Sign. Daoliang Li; Yingyi Chen. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-419 (Part I), pp.263-268, 2014, Computer and Computing Technologies in Agriculture VII. 〈10.1007/978-3-642-54344-9_32〉. 〈hal-01220927〉
