复杂背景图像中的车牌定位算法

针对复杂背景中的车牌定位问题提出了一种新的算法，将定位过程分解为确定候选车牌区域和剔除伪区域两个部分。首先在图像的二值垂直边缘图中，利用车牌区域的边缘信息及车牌的纹理特征进行车牌候选区域的确定，在降低算法复杂度的同时提高了定位精确性。然后，利用滑动的条带窗口对候选区域二值化图像进行连通块提取，结合车牌句法特征对该区域进行评判筛选，有效地解决了复杂背景及模糊图像中车牌定位精度不高的问题。此外，定位过程中的评判结果为后续的字符分割提供了重要的先验信息。实验证明该方法定位速度快，定位正确率高，对于背景纹理复杂及模糊图像的车牌定位具有很强的抗干扰性能。

License plate position algorithm in complicated scenes

A new algorithm for license plate position in complex backgrounds is proposed in this paper. The algorithm is decomposed into two parts, identification of candidate region and elimination of pseudo-region. The edge information and the texture features of license plate region are used to identify the candidate plates. The complexity of the algorithm is reduced and the accuracy of positioning is also improved. Then a sliding strip window is used to select connectivity blocks in the binary image of the candidate plate. And plate syntactic features are combined to evaluate the candidate plate. The low precision of license plate position in complex background and fuzzy image is solved effectively. Moreover, the results of the positioning provide important prior information for following character segmentation. Experimental results prove that the position method has good real-time performance and high positioning accuracy. In particular, it has strong robust performance for complex backgrounds and fuzzy images.