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MATLAB

于 2020-07-04 发布
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下载积分: 1 下载次数: 25

代码说明:

说明:  简易实现车牌识别,有GUI界面。车牌识别系统将获取的车辆图像进行一系列的处理后,以字符的形式输出结果(Simple license plate recognition with GUI interface.The license plate recognition system processes the acquired vehicle image in a series of ways and outputs the results in the form of characters.)

文件列表:

MATLAB, 0 , 2018-12-25
MATLAB\1.jpg, 849 , 2018-10-31
MATLAB\1.车牌灰度图像.jpg, 6488 , 2018-10-31
MATLAB\2.jpg, 765 , 2018-10-31
MATLAB\2.车牌二值图像.jpg, 8745 , 2018-10-31
MATLAB\3.jpg, 678 , 2018-10-31
MATLAB\4.jpg, 783 , 2018-10-31
MATLAB\4.均值滤波后.jpg, 8233 , 2018-10-31
MATLAB\5.jpg, 732 , 2018-10-31
MATLAB\5.膨胀或腐蚀处理后.jpg, 8233 , 2018-10-31
MATLAB\6.jpg, 846 , 2018-10-31
MATLAB\7.jpg, 820 , 2018-10-31
MATLAB\8.jpg, 876 , 2018-10-22
MATLAB\a.jpg, 768 , 2018-10-22
MATLAB\bg.jpg, 131428 , 2018-10-29
MATLAB\bg2.jpg, 91857 , 2018-10-29
MATLAB\car, 0 , 2018-12-25
MATLAB\car.xlsx, 8766 , 2018-10-22
MATLAB\car\car1.jpg, 144140 , 2018-10-21
MATLAB\car\car2.jpg, 144537 , 2018-10-21
MATLAB\car\car3.jpg, 217736 , 2018-10-21
MATLAB\dw.jpg, 8231 , 2018-10-31
MATLAB\getword.m, 870 , 2018-10-22
MATLAB\gui.fig, 46511 , 2018-10-29
MATLAB\gui.m, 16636 , 2018-10-29
MATLAB\main.m, 9198 , 2018-10-21
MATLAB\main0.m, 1789 , 2018-10-22
MATLAB\main02.m, 1041 , 2018-10-15
MATLAB\main1.m, 2655 , 2018-10-22
MATLAB\main10.m, 335 , 2018-10-22
MATLAB\main3.m, 5002 , 2018-10-22
MATLAB\main4.m, 1980 , 2018-10-22
MATLAB\main5.m, 7297 , 2018-10-22
MATLAB\q.jpg, 765 , 2018-10-22
MATLAB\qiege.m, 562 , 2018-10-21
MATLAB\sample, 0 , 2018-12-25
MATLAB\sample1, 0 , 2018-12-25
MATLAB\sample1\0.jpg, 8964 , 2018-10-22
MATLAB\sample1\1.jpg, 18188 , 2018-04-20
MATLAB\sample1\2.jpg, 820 , 2018-10-22
MATLAB\sample1\3.jpg, 18972 , 2018-04-20
MATLAB\sample1\4.jpg, 792 , 2018-04-20
MATLAB\sample1\5.jpg, 743 , 2018-10-22
MATLAB\sample1\6.jpg, 18887 , 2018-04-20
MATLAB\sample1\7.jpg, 624 , 2018-10-22
MATLAB\sample1\8.jpg, 846 , 2018-10-22
MATLAB\sample1\9.jpg, 778 , 2018-04-20
MATLAB\sample1\A.jpg, 792 , 2018-04-20
MATLAB\sample1\B.jpg, 848 , 2018-10-22
MATLAB\sample1\C.jpg, 19585 , 2018-04-20
MATLAB\sample1\D.jpg, 8503 , 2018-10-22
MATLAB\sample1\E.jpg, 652 , 2018-10-22
MATLAB\sample1\F.jpg, 18948 , 2018-04-20
MATLAB\sample1\G.jpg, 20077 , 2018-04-20
MATLAB\sample1\H.jpg, 600 , 2018-10-22
MATLAB\sample1\I.jpg, 17198 , 2018-04-20
MATLAB\sample1\J.jpg, 19189 , 2018-04-20
MATLAB\sample1\K.jpg, 19310 , 2018-04-20
MATLAB\sample1\L.jpg, 18762 , 2018-04-20
MATLAB\sample1\M.jpg, 18856 , 2018-04-20
MATLAB\sample1\N.jpg, 19539 , 2018-04-20
MATLAB\sample1\O.jpg, 17198 , 2018-04-20
MATLAB\sample1\P.jpg, 19701 , 2018-04-20
MATLAB\sample1\Q.jpg, 19857 , 2018-04-20
MATLAB\sample1\R.jpg, 12765 , 2018-10-22
MATLAB\sample1\S.jpg, 867 , 2018-04-20
MATLAB\sample1\T.jpg, 18678 , 2018-04-20
MATLAB\sample1\U.jpg, 8494 , 2018-10-22
MATLAB\sample1\V.jpg, 758 , 2018-10-22
MATLAB\sample1\W.jpg, 19575 , 2018-04-20
MATLAB\sample1\X.jpg, 19556 , 2018-04-20
MATLAB\sample1\Y.jpg, 655 , 2018-10-22
MATLAB\sample1\Z.jpg, 19037 , 2018-04-20
MATLAB\sample1\京.jpg, 18907 , 2018-04-20
MATLAB\sample1\津.jpg, 19126 , 2018-04-20
MATLAB\sample1\浙.jpg, 19136 , 2018-04-20
MATLAB\sample1\皖.jpg, 860 , 2018-10-22
MATLAB\sample1\粤.jpg, 19118 , 2018-04-20
MATLAB\sample1\苏.jpg, 828 , 2018-10-08
MATLAB\sample1\ԥ.jpg, 913 , 2018-04-20
MATLAB\sample1\辽.jpg, 705 , 2018-04-20
MATLAB\sample1\鄂.jpg, 19013 , 2018-04-20
MATLAB\sample1\陕.jpg, 894 , 2018-04-20
MATLAB\sample1\³.jpg, 19095 , 2018-04-20
MATLAB\sample\0.bmp, 640 , 2018-10-08
MATLAB\sample\1.bmp, 2454 , 2014-04-24
MATLAB\sample\2.bmp, 1878 , 2014-12-30
MATLAB\sample\3.bmp, 1878 , 2014-12-30
MATLAB\sample\4.bmp, 1878 , 2014-12-30
MATLAB\sample\5.bmp, 753 , 2018-10-08
MATLAB\sample\6.bmp, 1878 , 2014-12-30
MATLAB\sample\7.bmp, 1878 , 2014-12-30
MATLAB\sample\8.bmp, 876 , 2018-10-08
MATLAB\sample\9.bmp, 1878 , 2014-12-30
MATLAB\sample\A.bmp, 788 , 2018-10-08
MATLAB\sample\B.bmp, 798 , 2018-10-08
MATLAB\sample\C.bmp, 1878 , 2014-12-30
MATLAB\sample\D.bmp, 1878 , 2014-12-30
MATLAB\sample\E.bmp, 648 , 2018-10-08
MATLAB\sample\F.bmp, 1878 , 2014-12-30

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发表评论

0 个回复

  • caiyangdianshu
    当信号采样点数很少时,不能很好的恢复原模拟信号,导致原始信号中的一部分丢失。而当信号的采样点数增多到1024时,其分辨率很好,可以有效的区分信号的信息,当采样点数继续增多时,其恢复为原始模拟信号的精度越高且不丢失原始信号。(When the signal is small when the sampling points can not be good to restore the original analog signal, causing part of the original signal is lost. When the signal is increased to 1024 sampling points, its resolution is very good, can effectively distinguish the signal information, continue to increase when the sampling points, its back to the higher accuracy of the original analog signal without loss of the original signal.)
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    MATLABd得一些算法 10个经典的算法 一起学习啦(MATLABd have some classic algorithm 10 algorithms to learn啦)
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