Robust traffic sign detection using fuzzy shape recognizer

Lunbo Li; Jun Li; Jianhong Sun

doi:10.1117/12.833428

30 October 2009 Robust traffic sign detection using fuzzy shape recognizer

Lunbo Li, Jun Li, Jianhong Sun

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74960Z (2009) https://doi.org/10.1117/12.833428
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

A novel fuzzy approach for the detection of traffic signs in natural environments is presented. More than 3000 road images were collected under different weather conditions by a digital camera, and used for testing this approach. Every RGB image was converted into HSV colour space, and segmented by the hue and saturation thresholds. A symmetrical detector was used to extract the local features of the regions of interest (ROI), and the shape of ROI was determined by a fuzzy shape recognizer which invoked a set of fuzzy rules. The experimental results show that the proposed algorithm is translation, rotation and scaling invariant, and gives reliable shape recognition in complex traffic scenes where clustering and partial occlusion normally occur.

Citation Download Citation

Lunbo Li, Jun Li, and Jianhong Sun "Robust traffic sign detection using fuzzy shape recognizer", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960Z (30 October 2009); https://doi.org/10.1117/12.833428

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