A Method for the Fusion of Results from RFID and VLPR. Issue 1 (1st February 2023)

• Record Type: Journal Article
• Authors: Wang, Jia; Zhang, Hong; Zou, Huayi; Jiang, Suiping
• Is Part Of: Journal of physics. Volume 2425:Issue 1(2023)
• Publication Date: 2023-02-01
• Subjects: Radio Frequency Identification -- Vehicle License Plate Recognition -- Intelligent Transportation System -- Data Fusion -- Vehicle License Plate Matching.; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2425/1/012050
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Radio Frequency Identification (RFID) and Vehicle License Plate Recognition (VLPR) are two main methods for vehicle identification. How to fusion the recognition results of the two methods is a problem that needs to be solved in practice. The existing fusion technology usually uses trigger acquisition for precise matching, or uses one recognition result as a reference to perform matching in another result set, while these technology does not provide a clearly algorithm or has certain limitations, and is not universal. A matching algorithm is presented in this paper, which takes advantage of the similarity metric between the results from RFID and VLPR, thus eliminating the drawbacks of existing match methods. The algorithm calculates the similarity metric of the results from RFID and VLPR by the vehicle license plate character graphics similarity, then find matching results from the two recognition results in a specific time window, finally work out precise matching result or similar matching result. The presented algorithm is simple but effective, with no need to triggering RFID and VLPR simultaneously. The algorithm can output both precise matches and similar matches. Through the verification results in the real road scene, the performance in the license plate similarity calculation and fusion matching process is consistent with expectations, which shows the effectiveness of the algorithm.