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A new algorithm for license plate recognition based on improved edge detection and Mathematical morphology

机译:基于改进的边缘检测和数学形态学的车牌识别新算法

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This paper describes the advantages and disadvantages of current vehicle license plate location algorithms. To problems of inaccurating in Location of the vehicle plate, a method of image segmentation and extraction based on improved edge detection and Mathematical morphology was presented. In the first place, a series of color images were changed into gray images, secondly, through calculates the difference of each pixel and neighborhood pixels to buildup images' edge, and it can make the license plate stand out; once again, by adding the original image of the the results map which enhanced edge image, and it uses Sobel operator to extract the edge of objects in image; then the algorithm applies the dilation and erosion mathematical morphology of binary images to get the the image smooth contour; finally, from locating the position area alignment in the X and Y directions to locating license plates, meanwhile, using the median filter and the dilation and erosion mathematical morphology, and template matching algorithm to recognize the license plate character. Because of the accuracy of the plate region extraction, the character can be extracted exactly from the plate region. It can improve the accuracy rate of the characters recognition. From the results of simulation, it is found that the new method proposed in this thesis is efficient.
机译:本文描述了当前车辆牌照定位算法的优缺点。针对车牌定位不准确的问题,提出了一种基于改进的边缘检测和数学形态学的图像分割与提取方法。首先,将一系列的彩色图像转换为灰度图像,其次,通过计算每个像素与邻域像素的差值来构建图像的边缘,从而使车牌脱颖而出。再次通过添加结果图的原始图像来增强边缘图像,并使用Sobel运算符提取图像中对象的边缘;然后应用二值图像的膨胀和腐蚀数学形态学获得图像平滑轮廓。最后,从定位在X和Y方向上的位置区域对齐到定位车牌,同时,使用中值滤波器,膨胀和腐蚀数学形态学以及模板匹配算法来识别车牌特征。由于印版区域提取的准确性,因此可以从印版区域中准确提取字符。可以提高字符识别的准确率。从仿真结果可以看出,本文提出的新方法是有效的。

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