复杂背景下的车牌定位和字符分割研究

Research of Vehicle License Plate Location and Character Segmentation Under Complex Scenes

提出了一种综合边缘检测、投影特征的车牌定位方法和基于垂直投影及模板匹配的字符分割方法,提取车牌灰度图像边缘,实验结果显示该算法检测边缘的速度快,车牌区域轮廓清晰,采用投影法确定车牌区域,用HOUGH变换检测倾斜角度进而对倾斜的车牌进行矫正,通过字符分割算法对车牌字符进行切割,有效地解决了复杂环境的干扰、车牌尺寸变化等问题。对不同背景下的光照车牌进行了大量实验,结果表明该算法能准确地进行车牌定位以及字符分割,具有较好的鲁棒性。

An edge detection-projection feature based algorithm to locate the LP and a vertical projection-template matching algorithm to segment the characters are proposed, The edges are detected in a gray-level vehicle image, the result of experiment shows that the speed of detecting license plate is high and the obtained contour is very legible. The LP region is located by projection method, the tilt angle of LP is corrected by Hough transform. The character is segmented by LP segmentation algorithm, and some problems are solved effectively under complex scenes. To demonstrate the effectiveness of the proposed algorithm, it conducts extensive experiments over a large number of real-world vehicle license plates. It reports that the proposed algorithms have high accuracy and robustness.