Research of the methods of character recognition for landmark encoding
Industrial Electronics and Applications（2012）
摘要
The character recognition in landmarks is one of the key technologies in automatic navigation. After introducing the landmark recognition system, the character recognition algorithm based on the multiple perceptron neural network is presented. First of all, the algorithm is simulated in MATLAB, and the weights and thresholds for the sampled landmark character are obtained by training the perceptron neural network. Then, the weights and thresholds are burned to the ROM in the FPGA application board. Finally, in the Quartus II platform, the program based on HDL language is designed to complete the character recognition in this FPGA application board. The experimental results show that the system implements the real-time character recognition with high stability and robustness.
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关键词
real-time character recognition,rom,landmark character recognition,hdl language,perception network,matlab,monitoring pattern classifier,learning (artificial intelligence),landmark encoding,quartus ii platform,hardware description languages,character recognition,training,encoding,automatic navigation,mathematics computing,sampled landmark character,computer vision,fpga application board,landmark recognition system,perceptron neural network,field programmable gate arrays,multiple a network,perceptrons,learning artificial intelligence,hardware,read only memory
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