Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Research on Car Emblem Recognition Algorithm

Author LiYing
Tutor LiWenJu
School Liaoning Normal University
Course Applied Computer Technology
Keywords Car emblem recognition Knowledge Systems Neural Networks Inference engine Manifold Learning
CLC TP391.41
Type Master's thesis
Year 2007
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With economic development , the number of vehicles increases sharply , traffic problems have become increasingly prominent , which makes intelligent transportation system has become a hot research field , by the increasingly widespread concern . Vehicle identification is one of the important research topics in the field of intelligent transportation applications , is the core component of the intelligent transportation system , and can be widely used in dealing with traffic accidents , illegal vehicle monitoring , vehicle management , such as parking , airports , ports , residential entrance very broad application prospects . The vehicle identification information of the need to maximize the use of the vehicle to confirm the vehicle on a road . But only used the license plate and vehicle information , vehicle there is a more important message is that the car emblem information . The car emblem are the important information of the vehicle , is an iconic image of the vehicle , it contains not only the vehicle information, it is more important is that also contains the information of the manufacturer and it is difficult to replace . The combination car emblem , license plate and vehicle information , and will greatly improve the reliability of the vehicle identification . The car emblem picture carefully research a car emblem based on knowledge of the neural network recognition algorithm and a study based on the popular car emblem recognition algorithm . The car emblem recognition algorithm based on knowledge of the neural network as the theoretical framework of the theory of knowledge systems , is composed of two parts of the knowledge base and the inference engine . Knowledge base is used to store the used car emblem recognition knowledge , this paper to extract the car emblem gap and contour features for BP neural network training , sample car emblem contour feature , after a the car emblem gap number of characteristics and training The neural network weights to build the knowledge base . The inference engine is the use of knowledge in the knowledge base of the car emblem identify . Experiments prove that this method is not only to identify fast and high recognition rate . The car emblem recognition algorithm based on manifold learning is the picture of the sample , and to be recognized car emblem data dimensionality reduction processing , the car emblem picture identification operation in low-dimensional space , thus greatly reducing the computational amount of data use pictures of the car emblem texture information . The experimental results demonstrate the feasibility of the method .

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