J. Wang, G. Sun, L. Xu, and G. Li (PRC)
Neural network, traffic sign recognition, imagesegmentation, outline features, and moment invariants
According to color and geometric attributes of traffic signs in China, an efficient traffic sign recognition system applying to natural scenes is proposed in this paper. In this system, an improved image segmentation algorithm based on RGB color space is introduced to segment and extract possible regions of traffic signs in natural scene. Moreover, a two-level neural network is used to classify and recognize traffic signs, respectively. Outline features and moment invariants are used as inputs of classification neural network and recognition neural network, respectively. The experimental results demonstrate that the system is capable of achieving a good recognition for traffic signs in natural scene; furthermore, it has high robustness and broad applicability.
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