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Vehicle License Plate Recognition Based on Wavelet Transform and Vertical Edge Matching

机译:基于小波变换和垂直边缘匹配的车辆牌照识别

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摘要

With the improvement of our country's economic level and quality of life, the numbers and scales of highway networks and motor vehicles are constantly expanding, which makes the current road traffic burden more and more serious. As an important means of traffic automation management, license plate recognition (LPR) technology plays an important role in traffic surveillance and control. However, the recognition rate and accuracy of the traditional license plate recognition methods still need to be improved. In the case of poor surrounding environment, it is prone to localization failure, vehicle license plate recognition errors or unrecognizable phenomena. Wavelet transform, as another landmark signal processing method after Fourier transform, has been widely used in the field of image processing. In China, the number of horizontal lines is usually larger than that of vertical lines. If the two vertical boundaries of the license plate can be detected successfully, the four angles of the license plate can be determined efficiently to complete the license plate positioning. In view of the advantages of wavelet transform technology and the characteristics of vehicle license plate, in this paper, a vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching is proposed. The edge of the license plate is detected by wavelet transform technology, and then the license plate is located by vertical edge matching technology. After the location is realized, the characters are segmented by vertical projection method and the characters are recognized by improved BP neural network algorithm. The experimental results show that the proposed vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching performs well in algorithm performance, which provides a good reference for the development of vehicle license plate recognition system.
机译:随着我国经济水平和生活质量的提高,公路网络和机动车的数量和尺度不断扩大,这使目前道路交通负担越来越严重。作为交通自动化管理的重要手段,车牌识别(LPR)技术在交通监测和控制中起着重要作用。然而,仍需要改善传统车牌识别方法的识别率和准确性。在周围环境较差的情况下,它易于定位失败,车辆车牌识别错误或无法辨认的现象。小波变换作为傅里叶变换后的另一个地标信号处理方法,已广泛用于图像处理领域。在中国,水平线的数量通常大于垂直线的数量。如果可以成功检测牌照的两个垂直边界,则可以有效地确定牌照的四个角度以完成牌照定位。鉴于小波变换技术的优点和车辆牌照的特点,提出了一种基于小波变换和垂直边缘匹配的车辆牌照识别算法。用小波变换技术检测牌照的边缘,然后牌照由垂直边缘匹配技术定位。在实现位置之后,字符被垂直投影方法分段,并且通过改进的BP神经网络算法识别字符。实验结果表明,基于小波变换和垂直边缘匹配的基于小波变换的车辆牌照识别算法在算法性能下进行了良好的,这为车辆车牌识别系统的开发提供了良好的参考。

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