首页> 外文会议>Advances in Neural Networks - ISNN 2007 pt.2; Lecture Notes in Computer Science; 4492 >A New Text Detection Approach Based on BP Neural Network for Vehicle License Plate Detection in Complex Background
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A New Text Detection Approach Based on BP Neural Network for Vehicle License Plate Detection in Complex Background

机译:基于BP神经网络的复杂背景下车牌文本检测新方法。

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摘要

With the development of Intelligent Transport Systems (ITS), automatic license plate recognition (LPR) plays an important role in numerous applications in reality. In this paper, a coarse to fine algorithm to detect license plates in images and video frames with complex background is proposed. First, the method based on Component Connect (CC) is used to detect the possible license plate regions in the coarse detection. Second, the method based on texture analysis is applied in the fine detection. Finally, a BP Neural Network is adopted as classifier, parts of the features is selected based on statistic diagram to make the network efficient. The average accuracy of detection is 95.3% from the images with different angles and different lighting conditions.
机译:随着智能运输系统(ITS)的发展,自动车牌识别(LPR)在现实中的众多应用中都扮演着重要角色。提出了一种从粗到精算法,对背景复杂的图像和视频帧中的车牌进行检测。首先,基于组件连接(CC)的方法用于在粗略检测中检测可能的车牌区域。其次,将基于纹理分析的方法应用于精细检测。最后,采用BP神经网络作为分类器,根据统计图选择部分特征以提高网络效率。从不同角度和不同光照条件下的图像中,平均检测精度为95.3%。

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