This project forked from xiaoyixiaoyang/opencvexamples
OpenCV+交通标志识别
通过OpenCV预处理方法非线性变换改善图像的光照不良情况，颜色空间定位、形态学处理，轮廓筛选确定交通标志的最小外接矩形，辅以深度学习训练德国交通标志数据集，最终完成对输入图像的中存在的交通标志含义识别。
主要基于德国交通标志数据集训练，训练方法采用BP神经网络的训练方法
特色在于在颜色空间中分开寻找红黄蓝标志
分开二值化、形态学运算
最后放在一起筛选轮廓，得到各个标志的最小外接矩形
这样做的好处是有效分割了红黄蓝三个标志紧挨在一起的情况，但是两个红的挨在一起还是不行，后续形态学操作还会把两个形状融在一块
改进方法：将颜色空间中每种颜色找到的二值图分别作为一个对象去处理，这样既有效分割了红黄蓝三个标志紧挨在一起的情况，也分割了两个红的挨在一起的情况，后续形态学操作都是单独的
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