MobLP:一种基于cc的从手机摄像头获取的图像中分割车牌号码的方法

Abhishek Sharma, A. Dharwadker, T. Kasar
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引用次数: 3

摘要

过去已经开发了几种车牌识别系统。我们的目标是设计一个系统实现在一个标准的配备摄像头的移动电话,能够识别车辆牌照号码。作为第一步,我们提出了一种车牌文本分割方法,该方法对各种光照条件、由于LP肮脏或生锈而导致的复杂背景和非常规字体具有鲁棒性。在印度的情况下,一些车主选择用当地语言书写车牌号码。由于我们的方法不依赖于特定于语言的特性,因此它能够分割用不同语言编写的许可证编号。利用颜色连接分量标记、笔画宽度和文本启发式算法,我们完成了从车牌中准确分割车牌号码的任务。用带摄像头的手机采集的印度车牌图像进行了实验,实验结果表明,该系统在不同的车牌图像上表现良好,有些图像存在不同类型的退化。该方法对提取的LP数字文本进行OCR评价,准确率达到98.86%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MobLP: A CC-based approach to vehicle license plate number segmentation from images acquired with a mobile phone camera
Several License Plate Recognition systems have been developed in the past. Our objective is to design a system implemented on a standard camera-equipped mobile phone, capable of recognising vehicle license number. As a first step towards it we propose a license plate text segmentation approach that is robust to various lighting conditions, complex background owing to dirty or rusted LP and non-convential fonts. In the Indian scenario, some vehicle owners choose to write their vehicle number plates in regional languages. Since our method does not rely on language-specific features, it is therefore capable of segmenting license number written in different languages. Using color connected component labeling, stroke width and text heuristics we perform the task of accurately segmenting the number from the license plate. Experiments carried out on Indian vehicle license plate (LP) images acquired using a camera-equipped cellphone shows that our system peforms well on different LP images some with different types of degradations. OCR evaluation on the extracted LP number text with the proposed method has an accuracy of 98.86%.
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