低质量车牌字符分割技术研究
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摘要
随着信息技术和人工智能技术的发展,交通管理系统的信息化、智能化是大势所趋。车牌识别系统是智能交通系统的重要组成部分,在现代交通管理系统中占有举足轻重的地位。
车牌识别系统包括三个主要环节,即车牌定位、字符分割和字符识别,涉及五个关键技术,即图像预处理、车牌定位、倾斜校正、字符分割和字符识别。本文主要对车牌的倾斜校正和字符分割中涉及到的关键技术进行了深入的研究。
在获取车牌图像的过程中,由于摄像机和车牌之间角度的变化,经常使所拍摄的车牌图像发生倾斜,导致车牌扭曲和字符变形,给字符分割和识别带来困难。为此,本文提出了一种新的基于Radon变换的车牌倾斜校正算法。该算法对车牌图像进行Radon变换,并对变换后的结果求一阶导数绝对值的累加和,将累加和的最大值所对应的Radon变换的角度作为倾斜角度。实验结果证明,该算法简单实用,对光照、污迹等不敏感,抗干扰能力强。
字符分割是车牌识别系统的关键环节,是识别的基础,字符分割的效果直接决定了字符识别的准确率。本文提出了一种基于先验知识的质量退化的车牌字符分割算法,该算法利用垂直投影计算字符字段的个数,根据字符字段的个数和先验知识对车牌进行字符合并和字符分裂等操作。实验结果表明本算法对光照不均、对比度小、倾斜、污迹严重、车牌颜色退化严重、字符粘连和断裂等车牌有良好的字符分割效果。
在标准车牌字符分割的基础上,本文利用双行车牌的特性,提出了基于高斯拟合的双行车牌分割算法,利用高斯拟合求取双行车牌上下两行的分割位置,然后再分别利用基于先验知识的字符分割算法对上下两行进行字符分割。实验表明,该算法能够有效地分割出双行车牌的上下两行,并能对其进行有效的字符分割。
With the development of information technology and artificial intelligence technology, the informatization and intelligentization of traffic management system is a general trend. The license plate recognition (LPR) system is the core of the intelligent transportation system (ITS). It is very important in modern traffic management systems.
The LPR system consists of three steps and five key techniques. The steps are license plate location, character segmentation and character recognition. The key techniques are image preprocessing, license plate location, tilt correction, character segmentation and character recognition. The methods of license plate tilt correction and character segmentation are studied in this paper.
In the process of obtaining the license plate images, due to the angle change between the camera and the plate, the vehicle image usually tilts. This phenomenon leads to the distortion of the plate and the characters, and makes it difficult to the character segmentation and character recognition. A novel approach for vehicle license plate tilt correction based on Radon transform is proposed. Firstly Radon transformations are performed on the license plate image, and then the sum of absolute difference of the results is calculated, lastly the tilt angle is obtained by located the maximum. Experimental results show that this method is robust to the dirty license plates and the license plates under various lighting conditions, and it is practical.
As a key step of the LPR system, Character segmentation is the foundation of character recognition. The results of character segmentation determine the accuracy of recognition directly. This paper proposes a novel method for character segmentation of degraded license plate based on prior knowledge. Firstly character segments are located according to the vertical projection, and then the character segments are merged or split according to the vertical projection and the prior knowledge. This method is more efficient under the condition that the license plate images are degraded, such as uneven illumination, poor contrast, tilt, discoloration, fading, broken character, connected character, and etc.
Based on the standard license plate segmentation, this paper analyzes the characteristic of double rows license plate and proposes a method for double rows license plate segmentation based on Gaussian fitting. Segment position between the double rows is located by using Gaussian fitting, and then the characters of the double rows are segmented by using the standard license plate segmentation method. Experimental results show that this method is effective to segment the double rows.
车牌识别系统包括三个主要环节,即车牌定位、字符分割和字符识别,涉及五个关键技术,即图像预处理、车牌定位、倾斜校正、字符分割和字符识别。本文主要对车牌的倾斜校正和字符分割中涉及到的关键技术进行了深入的研究。
在获取车牌图像的过程中,由于摄像机和车牌之间角度的变化,经常使所拍摄的车牌图像发生倾斜,导致车牌扭曲和字符变形,给字符分割和识别带来困难。为此,本文提出了一种新的基于Radon变换的车牌倾斜校正算法。该算法对车牌图像进行Radon变换,并对变换后的结果求一阶导数绝对值的累加和,将累加和的最大值所对应的Radon变换的角度作为倾斜角度。实验结果证明,该算法简单实用,对光照、污迹等不敏感,抗干扰能力强。
字符分割是车牌识别系统的关键环节,是识别的基础,字符分割的效果直接决定了字符识别的准确率。本文提出了一种基于先验知识的质量退化的车牌字符分割算法,该算法利用垂直投影计算字符字段的个数,根据字符字段的个数和先验知识对车牌进行字符合并和字符分裂等操作。实验结果表明本算法对光照不均、对比度小、倾斜、污迹严重、车牌颜色退化严重、字符粘连和断裂等车牌有良好的字符分割效果。
在标准车牌字符分割的基础上,本文利用双行车牌的特性,提出了基于高斯拟合的双行车牌分割算法,利用高斯拟合求取双行车牌上下两行的分割位置,然后再分别利用基于先验知识的字符分割算法对上下两行进行字符分割。实验表明,该算法能够有效地分割出双行车牌的上下两行,并能对其进行有效的字符分割。
With the development of information technology and artificial intelligence technology, the informatization and intelligentization of traffic management system is a general trend. The license plate recognition (LPR) system is the core of the intelligent transportation system (ITS). It is very important in modern traffic management systems.
The LPR system consists of three steps and five key techniques. The steps are license plate location, character segmentation and character recognition. The key techniques are image preprocessing, license plate location, tilt correction, character segmentation and character recognition. The methods of license plate tilt correction and character segmentation are studied in this paper.
In the process of obtaining the license plate images, due to the angle change between the camera and the plate, the vehicle image usually tilts. This phenomenon leads to the distortion of the plate and the characters, and makes it difficult to the character segmentation and character recognition. A novel approach for vehicle license plate tilt correction based on Radon transform is proposed. Firstly Radon transformations are performed on the license plate image, and then the sum of absolute difference of the results is calculated, lastly the tilt angle is obtained by located the maximum. Experimental results show that this method is robust to the dirty license plates and the license plates under various lighting conditions, and it is practical.
As a key step of the LPR system, Character segmentation is the foundation of character recognition. The results of character segmentation determine the accuracy of recognition directly. This paper proposes a novel method for character segmentation of degraded license plate based on prior knowledge. Firstly character segments are located according to the vertical projection, and then the character segments are merged or split according to the vertical projection and the prior knowledge. This method is more efficient under the condition that the license plate images are degraded, such as uneven illumination, poor contrast, tilt, discoloration, fading, broken character, connected character, and etc.
Based on the standard license plate segmentation, this paper analyzes the characteristic of double rows license plate and proposes a method for double rows license plate segmentation based on Gaussian fitting. Segment position between the double rows is located by using Gaussian fitting, and then the characters of the double rows are segmented by using the standard license plate segmentation method. Experimental results show that this method is effective to segment the double rows.
引文
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