摘要：【中文】本发明公开了一种车牌识别方法及装置，所述方法包括：步骤S1，利用基于图像特征的局部车牌图像训练AdaBoost级联车牌分类器，利用车牌分类器对视频序列图片进行滑窗检测，得到视频序列图片中的车牌粗选区域；步骤S2，利用多尺度框融合方法，对得到的检测框进行合并，剔除低置信度度检测框；步骤S3，于得到融合后检测框后，在原始输入图像上切割出车牌区域图像，进行车牌精确定位；步骤S4，基于边缘检测算子对完成上下边界精确定位的图像提取字符边缘信息，得到完整车牌；步骤S5，根据二值化算法和连通域分析对精确定位的完整车牌进行字符切割；步骤S6，通过卷积神经网络识别切割字符，得到检测结果。 【EN】The invention discloses a license plate recognition method and a license plate recognition device, wherein the method comprises the following steps: step S1, training an AdaBoost cascade license plate classifier by using a local license plate image based on image characteristics, and performing sliding window detection on a video sequence picture by using the license plate classifier to obtain a license plate rough selection area in the video sequence picture; step S2, merging the obtained detection frames by using a multi-scale frame fusion method, and eliminating the detection frames with low confidence degrees; step S3, after the fused detection frame is obtained, a license plate region image is cut on the original input image, and license plate accurate positioning is carried out; step S4, extracting character edge information from the image with the accurate positioning of the upper and lower boundaries based on an edge detection operator to obtain a complete license plate; step S5, performing character cutting on the accurately positioned complete license plate according to a binarization algorithm and connected domain analysis; and step S6, recognizing the cutting characters through the convolutional neural network to obtain a detection result.