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chepai

于 2017-05-02 发布 文件大小:3355KB
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代码说明：

  基于MATLAB的汽车车牌牌照的识别。利用BP神经网络做GUI界面(Recognition of Vehicle License Plate License Based on. Using BP neural network to do GUI interface)

文件列表：

基于人工神经网络的汽车牌照识别MATLAB实现
........................................\汽车牌照识别程序
........................................\................\0.jpg
........................................\................\1.fig,1013267,2014-11-09
........................................\................\1.jpg
........................................\................\2.fig,51143,2014-11-09

........................................\................\3.fig,3436,2014-11-09

........................................\................\4.fig,17617,2014-11-09

........................................\................\5.fig,40112,2014-11-09
........................................\................\5.jpg,1127,2008-12-17
........................................\................\6.jpg,1243,2006-11-03
........................................\................\7.jpg,918,2006-11-03
........................................\................\8.jpg,1402,2006-11-03
........................................\................\9.jpg,1002,2006-11-03
........................................\................\A.jpg,1131,2008-12-17
........................................\................\AHE876.JPG,130342,2008-11-10
........................................\................\C.jpg,1010,2006-11-03
........................................\................\chepaidw.asv,1758,2008-12-06
........................................\................\DSC01317.JPG,140856,2006-11-03
........................................\................\DSC01318.JPG,136937,2006-11-03
........................................\................\DSC01319.JPG,129426,2006-11-03
........................................\................\DSC01320.JPG,131028,2006-11-03
........................................\................\DSC01321.JPG,147274,2006-11-03
........................................\................\DSC01322.JPG,130803,2006-11-03
........................................\................\DSC01323.JPG,141003,2006-11-03
........................................\................\DSC01324.JPG,123801,2006-11-03
........................................\................\DSC01327.JPG,123801,2008-11-10
........................................\................\G.jpg,1017,2006-11-03
........................................\................\H.jpg,770,2008-12-18
........................................\................\L.jpg,602,2006-11-03
........................................\................\location.asv,1754,2014-10-28
........................................\................\location.m,1752,2013-11-11
........................................\................\M.jpg,1032,2006-11-03
........................................\................\main.asv,2348,2014-11-09
........................................\................\main.m,2347,2014-11-09
........................................\................\N.jpg,932,2008-12-18
........................................\................\pretreatment.m,382,2008-12-19
........................................\................\R.jpg,1109,2006-11-03
........................................\................\StringSplit.m,1811,2013-11-11
........................................\................\Thumbs.db,254464,2014-10-31
........................................\................\Z.jpg,644,2014-10-31
........................................\................\渝.jpg,1339,2008-12-17
........................................\................\训练样本来源





........................................\................\............\DSC01328.JPG,129426,2008-11-10
........................................\................\............\Thumbs.db,31232,2014-10-28
........................................\程序说明.docx,13025,2014-11-09

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    转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)
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