? A Novel Fine-Grained Method for Vehicle Type Recognition Based on the Locally Enhanced PCANet Neural Network
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Journal of Computer Science and Technology 2018, Vol. 33 Issue (2) :335-350    DOI: 10.1007/s11390-018-1822-7
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A Novel Fine-Grained Method for Vehicle Type Recognition Based on the Locally Enhanced PCANet Neural Network
Qian Wang1,2,3, You-Dong Ding3,4, Senior Member, CCF
1 School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China;
2 Information Center, Criminal Investigation Department of Shanghai Public Security Bureau, Shanghai 200083, China;
3 Shanghai Engineering Research Center of Motion Picture Special Effects, Shanghai 200072, China;
4 Shanghai Film Academy, Shanghai University, Shanghai 200072, China

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Abstract In this paper, we propose a locally enhanced PCANet neural network for fine-grained classification of vehicles. The proposed method adopts the PCANet unsupervised network with a smaller number of layers and simple parameters compared with the majority of state-of-the-art machine learning methods. It simplifies calculation steps and manual labeling, and enables vehicle types to be recognized without time-consuming training. Experimental results show that compared with the traditional pattern recognition methods and the multi-layer CNN methods, the proposed method achieves optimal balance in terms of varying scales of sample libraries, angle deviations, and training speed. It also indicates that introducing appropriate local features that have different scales from the general feature is very instrumental in improving recognition rate. The 7-angle in 180° (12-angle in 360°) classification modeling scheme is proven to be an effective approach, which can solve the problem of suffering decrease in recognition rate due to angle deviations, and add the recognition accuracy in practice.
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Keywordsfine-grained classification   PCANet   local enhancement   vehicle type recognition     
Received 2016-10-11;
Corresponding Authors: 10.1007/s11390-018-1822-7   
About author: Qian Wang is a senior engineer in Information Center of Criminal Investigation Department of Shanghai Public Security Bureau, Shanghai, and also a Ph.D. candidate of School of Computer Engineering and Science, Shanghai University, Shanghai. Her research interests mainly include intelligent surveillance analysis, deep learning neural network, and intelligent human biological characteristic identification
Cite this article:   
Qian Wang, You-Dong Ding.A Novel Fine-Grained Method for Vehicle Type Recognition Based on the Locally Enhanced PCANet Neural Network[J]  Journal of Computer Science and Technology, 2018,V33(2): 335-350
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http://jcst.ict.ac.cn:8080/jcst/EN/10.1007/s11390-018-1822-7
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