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Proceedings Paper

License plate location based on improved visual attention model
Author(s): Zhenjie Yao; Weidong Yi
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Paper Abstract

License plate recognition (LPR) system play an important role in intelligent transportation systems (ITSs). It is difficult to locate a license plate in complex scene. Our location strategy integrates blue region, vertical texture and contrast features of LP in the framework of improved visual attention model. We improve visual attention model by changing normalization and linear combination into feature image binarization and logical operation. Multi-scale center-surround differences mechanism in visual attention model make the feature extraction robust. Tests on pictures captured by different equipments under different environments give delightful result, the success rate for location is as high as 95.28%.

Paper Details

Date Published: 13 January 2012
PDF: 7 pages
Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 834916 (13 January 2012); doi: 10.1117/12.920210
Show Author Affiliations
Zhenjie Yao, Graduate Univ. of the Chinese Academy of Sciences (China)
Weidong Yi, Graduate Univ. of the Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8349:
Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis
Zhu Zeng; Yuting Li, Editor(s)

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