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License-Plate-Recognition

License Plate Recognition For Car With Python And OpenCV

用python3+opencv3做的**车牌识别,包括算法和客户端界面,只有2个文件,surface.py是界面代码,predict.py是算法代码,界面不是重点所以用tkinter写得很简单。

使用方法:

版本:python3.4.4,opencv3.4和numpy1.14和PIL5
下载源码,并安装python、numpy、opencv的python版、PIL,运行surface.py即可

算法实现:

算法**来自于网上资源,先使用图像边缘和车牌颜色定位车牌,再识别字符。车牌定位在predict方法中,为说明清楚,完成代码和测试后,加了很多注释,请参看源码。车牌字符识别也在predict方法中,请参看源码中的注释,需要说明的是,车牌字符识别使用的算法是opencv的SVM, opencv的SVM使用代码来自于opencv附带的sample,StatModel类和SVM类都是sample中的代码。SVM训练使用的训练样本来自于github上的EasyPR的c++版本。由于训练样本有限,你测试时会发现,车牌字符识别,可能存在误差,尤其是第一个中文字符出现的误差概率较大。源码中,我上传了EasyPR中的训练样本,在train\目录下,如果要重新训练请解压在当前目录下,并删除原始训练数据文件svm.dat和svmchinese.dat。

额外说明:算法代码只有500行,测试中发现,车牌定位算法的参数受图像分辨率、色偏、车距影响(test目录下的车牌的像素都比较小,其他图片很可能因为像素等问题识别不了,识别其他像素的车牌需要修改config文件里面的参数,此项目仅是抛砖引玉,提供一个思路)。
有任何疑问请邮件至 [email protected]
界面效果:

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license-plate-recognition's Issues

获取车牌失败

只获得了车牌图片的颜色,没有获得车牌的具体信息

Can only detect his own test data

If I open an image in your own "test" folder, the system can return a result. However, if I choose any of my image, it fails. It seems that this project cannot recognise any new image?

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