License Plate Recognition Based On Prior Knowledge
In this paper, a new algorithm based on improved BP (back propagation) neural network for Chinese vehicle license plate recognition (LPR) is described. The proposed approach provides a solution for the vehicle license plates (VLP) which were degraded severely. What it remarkably differs from the traditional methods is the application of prior knowledge of license plate to the procedure of location, segmentation and recognition. Color collocation is used to locate the license plate in the image. Dimensions of each character are constant, which is used to segment the character of VLPs. The Layout of the Chinese VLP is an important feature, which is used to construct a classifier for recognizing. The experimental results show that the improved algorithm is effective under the condition that the license plates were degraded severely.
License plate recognition prior knowledge vehicle license plates neural network
Qian Gao Xinnian Wang Gongfu Xie
School of Information Engineering Dalian Maritime University Dalian,Liaoning Province, China
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18(万方平台首次上网日期,不代表论文的发表时间)