├── README.md ├── getword.m ├── main.m ├── my_imsplit.m ├── Ⅰ类文件分割 ├── 1.jpg ├── 2.jpg ├── 3.jpg ├── 4.jpg ├── 5.jpg ├── 6.jpg ├── 7.jpg ├── I类 │ ├── KW507.jpg │ ├── 京V02633.jpg │ ├── 京V02813.jpg │ ├── 冀B91999.jpg │ ├── 冀HN7491.jpg │ ├── 军A00101.jpg │ ├── 川A99999.jpg │ ├── 川R87979.jpg │ ├── 沪B87057.jpg │ ├── 辽A09030.jpg │ ├── 鄂AC8775.jpg │ ├── 鲁ENB911.jpg │ ├── 鲁JD9309.jpg │ └── 黑G77777.jpg ├── chuanA99999.m ├── chuanA99999 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ └── 7.jpg ├── heiG77777.m ├── heiG77777 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── junA00101.m ├── junA00101 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── luENB911.m ├── luENB911 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── luJD9309.m ├── luJD9309 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg └── 车牌图像.jpg ├── Ⅱ类文件分割 ├── II类 │ ├── 兰A20008.jpg │ ├── 冀BQQ613.jpg │ ├── 冀D06888.jpg │ ├── 晋F21696.jpg │ ├── 海O00000.jpg │ ├── 蒙A16777.jpg │ ├── 辽B57368.jpg │ ├── 鄂K9M555.jpg │ └── 鲁A88888.jpg ├── jinF21696.m ├── jinF21696 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── lanA20008.m ├── lanA20008 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── luA88888.m ├── luA88888 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── mengA16777.m └── mengA16777 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── Ⅲ类文件分割 ├── III类 │ ├── 云AU7526.jpg │ ├── 京K89779.jpg │ ├── 晋A00002.jpg │ ├── 晋AAS999.jpg │ ├── 晋C88888.jpg │ ├── 粤A3Y347.jpg │ └── 贵OA2803.jpg ├── jiC88888.m ├── jiC88888 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg ├── yunAU7526.m └── yunAU7526 │ ├── 1.jpg │ ├── 2.jpg │ ├── 3.jpg │ ├── 4.jpg │ ├── 5.jpg │ ├── 6.jpg │ ├── 7.jpg │ └── 车牌图像.jpg └── 车牌图像.jpg /README.md: -------------------------------------------------------------------------------- 1 | # matlab_test 2 | 基于matlab简易识别车牌 3 | 4 | 5 | 6 | 识别车牌大致步骤如下 7 | 8 | 第一步：从原图像中切割出车牌，去除无用信息 9 | 10 | 1.读取原图像。 11 | 12 | 2.将原始彩色图像转换成灰度图像，并显示直方图（如果分布十分不均匀，使用直方图均衡化处理）。 13 | 14 | 3．使用roberts算子进行边缘检测（MATLAB中调用edge函数）。 15 | 16 | 4．图像腐蚀（去除不需要的边缘信息，尽可能只保留车牌上字符的轮廓）。 17 | 18 | 5．图像膨胀（平滑图像轮廓，图中没能完全滤出车牌之外的所有边缘信息，剩下了一部分，其实就是车牌上的那个奥迪标志，后面还要想办法把它给去掉）。 19 | 20 | 6．从图像中移除小块对象（调用bwareaopen()函数，从图像中删除所有少于2200像素8邻接的区域，最后只剩下车牌区域了）。本图没有小块对象，就不用去除。 21 | 22 | 7．根据最后图像中“白色”的那部分界定车牌所处的区域，并重新在原图像中进行切割，得到车牌的图像。 23 | 24 | 第二步：从前面得到的车牌图像中切割出每个字符 25 | 1．先将车牌图像转换为灰度图像并绘制直方图。 26 | 27 | 2．为增强对比度，对灰度图像再做直方图均衡化。 28 | 29 | 3．将图像二值化 30 | 31 | 4．中值滤波，滤除一些无用信息。 32 | 33 | 5．调用编写的my_imsplit.m和getword.m脚本，计算每个字符的位置，并逐一进行切割，得到只储存单一字符的图像。 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