Vehicle Plate Detection in Car Black Box Video

Author:

Park Dongjin1,Jun Kyungkoo1ORCID

Affiliation:

1. Department of Embedded Systems Engineering, Incheon National University, Incheon, Republic of Korea

Abstract

Internet services that share vehicle black box videos need a way to obfuscate license plates in uploaded videos because of privacy issues. Thus, plate detection is one of the critical functions that such services rely on. Even though various types of detection methods are available, they are not suitable for black box videos because no assumption about size, number of plates, and lighting conditions can be made. We propose a method to detect Korean vehicle plates from black box videos. It works in two stages: the first stage aims to locate a set of candidate plate regions and the second stage identifies only actual plates from candidates by using a support vector machine classifier. The first stage consists of five sequential substeps. At first, it produces candidate regions by combining single character areas and then eliminates candidate regions that fail to meet plate conditions through the remaining substeps. For the second stage, we propose a feature vector that captures the characteristics of plates in texture and color. For performance evaluation, we compiled our dataset which contains 2,627 positive and negative images. The evaluation results show that the proposed method improves accuracy and sensitivity by at least 5% and is 30 times faster compared with an existing method.

Funder

Incheon National University

Publisher

Hindawi Limited

Subject

General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Intelligent Traffic Monitoring System using Infrared Automatic Number Plate Recognition (IR-ANPR);2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA);2023-12-21

2. Vehicle Number Plate Recognition Using Raspberry Pi;1;2023-03-01

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