Identification of Vehicle Types Based on Spiking Neural Network Model
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    Abstract:

    Accurate feature extraction and recognition of moving objects are the hot spots in image processing and artificial intelligence research domains. In order to identify the types of moving vehicles, this paper proposed an identification approach in which edges of the moving vehicle are extracted by a spiking neural network model. The line moment of moving vehicle is used as the features to train a neural network, and then the neural network is used to identify type of the moving vehicle. The results of the simulation show that the approach can accurately extract the features of the moving vehicles so that the accuracy of identification has been improved. This approach shows a promising prospect in the application of intelligent surveillance systems in the future.

    Reference
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陈浩,吴庆祥,王颖,林梅燕,蔡荣太.基于脉冲神经网络模型的车辆车型识别.计算机系统应用,2011,20(4):182-185

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History
  • Received:July 19,2010
  • Revised:August 31,2010
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