Automatic license plate recognition using mobile device

Hung Ngoc Do, Minh-Thanh Vo, B. Vuong, H. Pham, A. Nguyen, H. Q. Luong
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引用次数: 23

Abstract

The rapid development of intelligent transport systems (ITS) brings us a safer and more convenient life. In this field, automatic license plate recognition (ALPR) plays an important role in many applications which have been deployed in reality such as stolen car detection, parking system management, and automatic transport charging system. The traditional ALPR methods usually need a high resolution camera to capture good quality images and a powerful computer to process the complex algorithms. However, with many great scientific breakthroughs in mobile device technology, we can easily buy smartphone/tablet which equipped strong central processing unit (CPU) and excellent camera to meet the requirements of ALPR. In this paper, we develop an Android program which processes the image captured by built-in camera of mobile device to have license plate number and save it into database for further applications. Open-source OpenCV libraries are imported into project for some image processing steps with purpose of programming time saving. We apply Tesseract engine and neural network which are two optical character recognition (OCR) methods to convert license plate image to machine-encoded text.
使用移动设备自动识别车牌
智能交通系统(ITS)的快速发展为我们带来了更安全、更便捷的生活。在这一领域中,车牌自动识别(ALPR)在许多实际应用中发挥着重要的作用,如被盗车辆检测、停车系统管理、自动运输收费系统等。传统的ALPR方法通常需要高分辨率的相机来捕获高质量的图像,并需要强大的计算机来处理复杂的算法。然而,随着移动设备技术的许多重大科学突破,我们可以很容易地购买到配备强大中央处理器(CPU)和优秀摄像头的智能手机/平板电脑,以满足ALPR的要求。在本文中,我们开发了一个Android程序,该程序可以将移动设备内置摄像头拍摄的图像处理成具有车牌号码的图像,并将其保存到数据库中以供进一步应用。为了节省编程时间,将开源的OpenCV库导入到项目中进行一些图像处理步骤。应用Tesseract引擎和神经网络两种光学字符识别(OCR)方法将车牌图像转换为机器编码文本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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