Abstract:


Abstract: License plate recognition （LPR） is an important tool for vehicle information recognition. However， it faces some problems such as similar character confusion and unmeasurable credibility of recognition results. In order to improve the usability of LPR algorithms， this paper proposes a multi-result voting fusion method based on character similarity. The method calculates the voting weight of the LPR results according to the character similarity and Bayes theorem， and selects the largest voting weight as the voting result. In the process of calculating the voting weight， the plate weighted voting method and character weighted voting method are proposed according to the characteristics of license plate. Between them， the plate weighted voting method takes the whole license plate as the voting unit， and the character weighted voting method takes a single license plate character as the voting unit. At the same time， voting result confidence is calculated to measure the credibility of the voting results， and it is the theoretical minimum voting accuracy. The experimental results show that the proposed method can effectively reduce the confusion of character recognition. Compared with the traditional weighted voting method， the voting accuracy and error-prone character voting accuracy of the proposed method are increased by 0.78 percentage points and 2.18 percentage points respectively. The experimental results also show that the proposed voting result confidence calculation method is effective and stable. Compared with the traditional weighted voting method， the proposed method can better reflect the credibility of the voting results. 

Key words: Key words: character similarity, weighted voting, result fusion, license plate recognition