【作者】 国庆；

【导师】 尚赵伟；

【作者基本信息】 重庆大学 ， 计算机应用技术， 2010， 硕士

【摘要】 车辆牌照识别系统(LPR)作为一个专用的计算机视觉系统,能够自动地摄取车辆图像并识别出车牌。LPR系统的研究涉及数字图像处理、计算机视觉、模式识别与人工智能等多个技术领域,其关键技术包括车牌定位、字符分割、字符识别等。其中车牌定位是指将车牌区域从车辆图像中定位并分割出来,为后续操作提供了输入信息,是整个车牌识别系统的基础。本文在详细研究了国内外各种具有代表性的车牌定位方法基础上,结合中国车牌的特点提出了三种不同的车牌定位方法:①.《一种基于Top-hat变换的多车牌定位改进方法》:此方法以数学形态学为基础,用Top-hat变换来提取车牌信息,再通过平滑、二值化、垂直信息提取、连通、密度计算等多个操作完成车牌定位。②.《基于二进小波变换的多车牌定位算法》:以图像二进小波变换后的垂直方向高频子带为基础,通过后续去伪定位操作来精确定位车牌,实验表明此方法定位效果要远远好于传统的小波定位方法。③.《基于压缩域的多车牌定位技术》:该方法以JPEG格式的车牌图像中的DCT系数为研究对象。根据DCT变换的特性,从每一个8×8模块的DCT系数选取了6个代表此模块的纹理密度用以描述该模块的垂直纹理和对角纹理。再结合车牌自身纹理的特征来定位车牌。这三种方法各有优劣,适合于不同要求的车牌定位系统中。基于Top-hat变换的车牌定位实现简单,定位效果较好,适用范围广,通用性强,适用于实时的交通系统中。基于二进小波的车牌定位方法效果最好,但运算较复杂,耗时较多,适用于后台运作的交通系统中。基于压缩域的车牌定位方法,从压缩域出发,利用JPEG文件中DCT系数来获取交通图像中的车牌纹理特征,缩短了定位时间,且定位效果优于传统的定位算法。更多还原

【Abstract】 License plate recognition(LPR) is a special computer vision system, which can recognize the license plate automatically from the video。The study of LPR is related to many kinds of technologies such as digital image processing, computer vision, pattern recognition and artificial intelligence. Its key techniques include license plate location, character segmentation and recognition. License plate location, which is to locate and segment the License Plate from a vehicle image, providing the inputting information for the next processes, is the basis of LPR system.Based on the detail analysis of the typical LPR system over the world and the characteristics of Chinese license plate, three different algorithms of license plate location are presented in this paper:①.< The application of Top-hat Transform in Multi-license Plate Localization >: Combining with the texture feature of license plates and the characteristics of Top-hat transform, the Top-hat coefficients are retained. Then the license plate can be located through smoothing, vertical direction information, four connected region detection, and density calculation and so on. The proposed algorithm was suitable for the single-license and multi-license plate detection in various illumination conditions with high accuracy.②.<Multi-license Plate Localization Algorithm Based on Dyadic Wavelet Transform>:In this chapter a new algorithm which can improve the accuracy of vehicle license plate location using dyadic wavelet coefficients in vertical direction is presented. The performance of the proposed algorithm has been tested on monitoring images obtained from the practical application. Experimental results show that our algorithm has better performance than Mallat’s on location precision.③.<Multi-license Plate Localization Algorithm in compressed domain>: A new algorithm for license plate localization using the discrete cosines transform (DCT) coefficients is proposed in this section. According to the characteristic of DCT, six AC coefficients of an 8*8 block were selected to represent the vertical and diagonal textures of a block. Then following the next processes, the license plate would have been located at last.These three algorithms having their own advantages were suitable for the different LPR systems respectively. The algorithm based on Top-hat was easily realized and suitable for the real time LPR system. The algorithms based on dyadic wavelet transform performed best, but was complicated and time-consuming. So it was suitable for the background system. The algorithm based compressed domain using DCT coefficients in JPEG files to capture the license plate enhanced localization-efficiency rapidly. Although its effect was not as good as the two algorithms mentioned before, it was better than the traditional methods.更多还原