基于颜色和纹理分析的车牌定位方法

针对复杂背景的车牌定位问题，提出了一种颜色和纹理分析相结合的车牌定位算法。该算法采用基于适合彩色图象相似性比较的HSV颜色模型，首先在颜色空间进行距离和相似度计算；然后对输入图象进行颜色分割，只有满足车牌颜色特性的区域，才进入下一步的处理；最后再利用纹理及结构特征对分割出的颜色区域进行分析和进一步判断，并确定车牌区域。该方法不同于大多数的车牌定位方法，它不仅对车牌的大小、汽车在图象中的位置以及图象背景的限制较少，而且，综合特征定位要比单一特征定位更符合人的视觉要求，因而定位效果更好，应用范围更广。

Color and Texture Analysis Based Vehicle License Plate Location

This paper presents an effective license plate location algorithm, which employs color and texture analysis to extract the number plate from the complicated background image. Based on the HSV color model, the algorithm calculates the distance and the similarity in the color space to segment the color image. Only those parts of the input image that fulfill a set of license plate properties need to be considered for a more thorough inspection. To the segmented image, the texture and structural features are analyzed to locate the license plate correctly. The algorithm has been tested with 60 color image obtained from tollgete, crossroad and parking lot, etc. More than 95% image can be proceesed correctly, whereas other images are disturbed by the complex backgrounds of the images. It is shown that, different from most license plate location methods, the algorithm has fewer limits to the car size, the car position in the image and the image background. Meanwhile, with the fast focusing technique, the view angle of the video camera can cover a wider area while the processing time can still be fast. So, the algorithm can be employed to the applied vehicle license plate recognition system.