Title :
Detection for triangle traffic sign based on neural network
Author :
Zhu, Shuang-Dong ; Zhany, Yi ; Lu Xiao-feng
Author_Institution :
Fac. of Inf. Sci. & Technol., Ningbo Univ., China
Abstract :
This literature critically explains the intelligent method for detection of traffic signs. This method uses a particular color and shape for the detection of traffic signs, as an example, we used red color down triangle shape traffic sign, to explain this method. This method is mainly carried out in four steps, which are as follows. First, convert RGB color space to HIS color space, and extract pixels with red color. Then perform LOG mask operation on the pixels got from step 1, for the detection of edges. By using neural network, we determine the angle pixels, and at the same time, we also determine on which specific angle the pixel is. And finally we detect the traffic sign by using the information of shape. We used 20 different images from different scenes to test this method, and the percentage of correctness is 100%.
Keywords :
edge detection; image colour analysis; neural nets; road traffic; traffic engineering computing; RGB color space; edge detection; neural network; red color down triangle shape traffic sign; triangle traffic sign detection; Image edge detection; Image recognition; Layout; Machine intelligence; Neural networks; Nonlinear distortion; Pollution; Shape; Telecommunication traffic; Testing;
Conference_Titel :
Vehicular Electronics and Safety, 2005. IEEE International Conference on
Print_ISBN :
0-7803-9435-6
DOI :
10.1109/ICVES.2005.1563608