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投影点坐标方差最小化车牌垂直倾斜校正
引用本文:吴一全,丁坚.投影点坐标方差最小化车牌垂直倾斜校正[J].应用科学学报,2009,27(2):177-181.
作者姓名:吴一全  丁坚
作者单位:南京航空航天大学信息科学与技术学院,南京210016
摘    要:车牌识别中为便于字符分割与识别,需对倾斜车牌进行校正. 该文提出基于字符投影点坐标方差最小的车牌垂直倾斜校正方法. 首先对水平校正并划定字符区上下边界后的车牌图像进行字符粗分割,然后将字符点经剪切变换沿垂直方向投影. 根据投影点坐标方差最小导出两种剪切角闭合表达式,由此一步确定车牌垂直倾斜角并进行校正. 实验结果表明:与车牌垂直倾斜校正的旋转投影法和直线拟合法相比,该文提出的方法精确度高,运算时间少且鲁棒性好.

关 键 词:车牌识别  垂直倾斜校正  剪切变换  垂直投影  最小方差  
收稿时间:2008-01-28
修稿时间:2008-12-05

Vertical Tilt Correction for Vehicle License Plate Based on Minimizing Variance of Coordinates of Projection Points
WU Yi-quan,DING Jian.Vertical Tilt Correction for Vehicle License Plate Based on Minimizing Variance of Coordinates of Projection Points[J].Journal of Applied Sciences,2009,27(2):177-181.
Authors:WU Yi-quan  DING Jian
Institution:School of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract:In order to facilitate character segmentation and recognition in a license plate recognition system, the tilting license plates in the located images should be corrected in both the horizontal and vertical directions. A vertical tilt correction method by minimizing variance of coordinates of the projection points is proposed. Coarse character segmentation is performed after horizontal correction and upper and lower border delineation. The character points are projected along the vertical direction after shear transform. Two closed-form expressions of the shear angle are derived based on minimizing variance of coordinates of the projection points. Thus the vertical tilt angle is directly determined and the license plate images corrected using the vertical tilt angle. Experimental results show that, compared to the vertical tilt correction methods of the license plate based on rotation projection and line fitting, the proposed method has high accuracy, requires less computation, and is robust. The proposed method has been applied in practical engineering system.
Keywords:vehicle license plate recognition  vertical tilt correction  shear transform  vertical projection  minimum variance  
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