针对汽车车牌号与车身背景的分割问题,给出了一种基于小波分析和数学形态学的图象分割方法.该方法是通过小波多尺度分解提取出纹理清晰,具有不同空间分辨率、不同方向的边缘子图象.其水平方向低频、垂直方向高频的这一细节分量,主要代表车牌的目标区域.然后,用数学形态学方法对小波分解后的细节图象进行一系列的形态运算,进一步消除无用信息和噪声,以找准车牌位置.用该方法对在不同照明条件下所采集到的一系列车头、车尾图象进行了大量的实验.实验结果表明,该方法定位效果好,分割精度高,适于对有噪声的车牌图象进行分割.

In this paper, a kind of practical image segmentation algorithm for segmenting the license plate from its vehicle body background is presented, based on wavelet multiscale analysis and mathematical morphology. By multi-resolution analysis and pyramid decomposition, the edge components with different spatial resolutions and different directions can be acquired, among which, the horizontal low-frequency and vertical high-frequency component has the most distinguished texture feature standing for the object region of the license plate. Then by further morphological operations, the noise in these edge components can be greatly decreased and the locations of the license plates can be also accurately determined. We have completed a series of experiments under different conditions. The experiment results show that the segmentation effects and it' s orientation accuracy are improred significantly, so the proposed method is very effective for segmenting and locating noisy vehicle license plates.