中文摘要：

为克服车牌边框、铆钉、车牌倾斜及车牌图像中亮度不均等不利因素的影响,利用水平结构元素对图像进行灰度Top-hat/Bottom-hat形态学锐化增强;然后通过中间行扫描,对各连通体进行blob分析.在字符分割过程中,利用车牌字符高度整体一致、相邻字符水平位置基本一致以及相邻字符中心间距所特有的比例关系等整体特性,作为车牌字符分割的依据.可有效克服常用方法中单个字符特性及单个字符与车牌总体的相对特性对图像倾斜、拉伸、缩放敏感及难以处理字符中的＂1＂的缺陷,实验结果证明了该算法的有效性.

英文摘要：

In order to overcome the disadvantage influence bring by plate boundaries,rivets,slant of license plate and uneven brightness of image,firstly,the input image is sharpened by grayscale morphological Top-hat/Bottom-hat transform with a horizontal flat structural element to suppress the background and remove the horizontal boundaries of license plate,which will be advantageous to eliminating character conglutination after the successive OTSU binary threshold.Then,a blob analysis is performed to the connected region,from which the middle row passes through.In the end,all the characters are located and segmented by use of the whole properties of license plate characters in height,centre coordinate and the special proportion relation between the center intervals between two adjacent characters.These whole properties is put forward for the first time,they are different from those individual property of characters as they are not sensitive to image slant,image stretch and image zoom,and can not be influenced by character ＂1＂.Experimental results indicate that our algorithm is feasible and effective.