A New Text Detection Approach Based on BP Neural Network for Vehicle License Plate Detection in Complex Background
Identifieur interne : 000F18 ( Main/Merge ); précédent : 000F17; suivant : 000F19A New Text Detection Approach Based on BP Neural Network for Vehicle License Plate Detection in Complex Background
Auteurs : Yanwen Li [République populaire de Chine] ; Meng Li [République populaire de Chine] ; Yinghua Lu [République populaire de Chine] ; Ming Yang [République populaire de Chine] ; Chunguang Zhou [République populaire de Chine]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: With the development of Intelligent Transport Systems (ITS), automatic license plate recognition (LPR) plays an important role in numerous applications in reality. In this paper, a coarse to fine algorithm to detect license plates in images and video frames with complex background is proposed. First, the method based on Component Connect (CC) is used to detect the possible license plate regions in the coarse detection. Second, the method based on texture analysis is applied in the fine detection. Finally, a BP Neural Network is adopted as classifier, parts of the features is selected based on statistic diagram to make the network efficient. The average accuracy of detection is 95.3% from the images with different angles and different lighting conditions.
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DOI: 10.1007/978-3-540-72393-6_101
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In this paper, a coarse to fine algorithm to detect license plates in images and video frames with complex background is proposed. First, the method based on Component Connect (CC) is used to detect the possible license plate regions in the coarse detection. Second, the method based on texture analysis is applied in the fine detection. Finally, a BP Neural Network is adopted as classifier, parts of the features is selected based on statistic diagram to make the network efficient. The average accuracy of detection is 95.3% from the images with different angles and different lighting conditions.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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