根据车牌纹理及其几何形状的特点，设计了一种基于数学形态学的车牌图象分割方法，该方法在二维形态滤波过程中，能自适应地调整阈值大小，以适应光照强度及干扰强度的变化，同时把基于全像素点数学形态学处理的点运算转化成仅有几十条直线的线运算，以使运算速度和抗干扰能力较其他传统分析方法有显著提高．用该方法对不同照明条件下的一系列汽车图象进行的大量实验结果表明，该方法不仅定位效果好、速度高，而且适于对有噪声及复杂背景的车牌图象进行分割．

Aiming at plate texture and plate shape of vehicle image, an algorithm applied to license plate extraction of vehicle image based on mathematical morphology is introduced. It adapts to the complicated background of vehicle image and the variety of illuminating conditions by adjusting threshold, while two-dimensional morphological filtering method. Moreover, point operation of mathematical morphology is inverted into line operation of mathematical morphology, The binarization method is based on one-dimensional edge detection to effectively utilize the plate shape and plate texture feature of vehicle images. It is much more robust and faster than the traditional thresholding methods and edge detecting operator methods. We have completed a series of experiments under different conditions. The experiment results show that the segmentation effects and it's orientation accuracy are improved significantly, so the proposed method is very effective for segmenting and locating noisy vehicle license plates.