Automatic License-Plate Location and Recognition Based on Feature Salience

被引:64
作者
Chen, Zhen-Xue [1 ]
Liu, Cheng-Yun [1 ]
Chang, Fa-Liang [1 ]
Wang, Guo-You [2 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
[2] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Feature salience; feature selection; license-plate location; license-plate recognition (LPR);
D O I
10.1109/TVT.2009.2013139
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
License-plate recognition plays an important role in numerous applications, and a number of techniques have been proposed. In this paper, a novel method to recognize license plates is presented. First, the license plates are located using salient features. Then, each of the seven characters in a license plate is segmented. Finally, the character recognizer extracts some salient features of the characters and uses a feature-salience classifier to achieve robust recognition results. In the experiments, 1176 images that were taken from various scenes and conditions were used, and 32 images out of the 1176 images failed to correctly locate the license plates, which amounts to a success rate of 97.3%. In the experiments on identifying license characters, we used 1144 images, for which license plates have successfully been located and out of which 49 images failed to identify the characters; the rate of successful identification is 95.7%. Combining the preceding two rates, the overall rate of success of the developed method is 93.1%.
引用
收藏
页码:3781 / 3785
页数:5
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