首页> 外文会议>Proceedings of the 2010 Annual IEEE India Conference >MobLP: A CC-based approach to vehicle license plate number segmentation from images acquired with a mobile phone camera
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MobLP: A CC-based approach to vehicle license plate number segmentation from images acquired with a mobile phone camera

机译:MobLP:一种基于CC的方法,用于从使用手机摄像头获取的图像中进行车牌号分割

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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%.
机译:过去已经开发了几种车牌识别系统。我们的目标是设计在配备标准相机的手机上实现的系统,能够识别车辆许可证号。作为迈出它的第一步,我们提出了一种许可证文本细分方法,这是对各种照明条件,由于脏或生锈的LP和非对流字体而复杂的背景是强大的。在印度方案中,一些车主选择以区域语言编写其车辆号码板材。由于我们的方法不依赖于语言特定功能,因此它能够分割以不同语言编写的许可证号码。使用彩色连接组件标签,笔划宽度和文本启发式信息我们执行准确地分割许可板的任务。在使用相机的手机获取的印度车辆牌照(LP)图像上进行的实验表明,我们的系统PEFORMS在不同类型的降级类型的不同LP图像上井。用提出的方法对提取的LP编号文本的OCR评估具有98.86%的精度。

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