Moving Vehicle License Plate Recognition Based on Parallel Integrated Multi-classifier
In the process of moving vehicle license plate recognition,the sequential images get degraded generally, due to the movement and influence of lacking illumination and smut. It is difficult to recognize the number of vehicle license plate correctly by those common classifiers. A new integrated classifier proposed here based on multi-feature and multi-structure is applied to recognize moving vehicles license plates. The recognition correction rate of license plate is exceeded 94％ in experiments. Statistical recognition results show, compared with common single-structured classifiers, this new integrated scheme is able to improve the recognition performance of single character and license plate number.
Character Recognition License Plate Recognition Neural Network Classifier Integration
Tongneng He Nengneng Liu Defu Chen
Department of Information Engineering, Zhejiang University of Technology, Hangzhou, 310014, China School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shangha
国际会议
杭州
英文
701-704
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）