登录
首页 » matlab » MATLAB车牌识别[算法对比,GUI]

MATLAB车牌识别[算法对比,GUI]

于 2020-08-06 发布
0 359
下载积分: 1 下载次数: 16

代码说明:

说明:  该课题为基于MATLAB的汽车出入库识别系统,带有丰富的人机交互GUI界面。目前毕业设计选题中,传统的中规中矩的车牌识别不易得到高分,必须要在此基础上有所创新方得可以避开其他雷同课题,不会轻易被导师被否决而导致毕设不过。因此建议在车牌识别基础上加入多种方法的对比,看看哪种方法的精度高。虽然目前有很多方法的车牌识别,但是都是在各自的测试库里面测试的,比如测试的车牌图像不同,字符库不同,导致无法做对比。整个设计在一个GUI界面上完成。(This project is based on MATLAB vehicle in and out of the warehouse identification system, with rich human-computer interaction GUI interface. At present, in the topic selection of graduation project, the traditional regular license plate recognition is not easy to get high scores, so it is necessary to innovate on this basis to avoid other similar topics, and it will not be rejected easily by the tutor, leading to the failure of graduation project. Therefore, it is suggested to add a variety of methods on the basis of license plate recognition to see which method has high accuracy. Although there are many methods of license plate recognition, they are tested in their own test library, for example, the test license plate image is different, the character library is different, so it can not be compared. The whole design is completed on a GUI interface.)

文件列表:

MATLAB车牌识别[算法对比,GUI], 0 , 2020-07-30
MATLAB车牌识别[算法对比,GUI]\源码GUI, 0 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\1.jpg, 533 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\2.jpg, 636 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\3.jpg, 633 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\4.jpg, 634 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\5.jpg, 573 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\6.jpg, 637 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\7.jpg, 637 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\after average licence plate.jpg, 2344 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\binary licence plate.jpg, 2511 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\chepaishibiegui.fig, 23538 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\chepaishibiegui.m, 11878 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\dw.jpg, 2440 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\example, 0 , 2020-07-30
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\1.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\10.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\11.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\12.bmp, 1592 , 2008-11-04
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\13.bmp, 1592 , 2008-11-04
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\14.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\15.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\16.bmp, 1592 , 2008-10-18
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\17.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\18.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\19.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\2.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\20.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\21.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\22.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\23.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\24.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\25.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\26.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\27.bmp, 1590 , 2008-10-21
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\28.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\29.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\3.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\30.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\31.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\32.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\33.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\34.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\35.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\36.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\37.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\38.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\39.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\4.bmp, 1592 , 2008-10-18
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\40.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\41.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\42.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\43.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\44.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\45.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\46.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\47.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\48.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\49.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\5.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\50.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\51.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\52.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\53.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\54.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\55.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\56.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\57.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\58.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\59.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\6.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\60.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\61.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\62.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\63.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\64.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\65.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\66.bmp, 1590 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\67.bmp, 1592 , 2008-10-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\7.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\8.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\example\9.bmp, 1592 , 2008-10-17
MATLAB车牌识别[算法对比,GUI]\源码GUI\expansion or corrosion the licence plate.jpg, 2547 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\getword.m, 920 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\gray licence plate.jpg, 1866 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\per_deal.m, 254 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\qiege.m, 542 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\wordprocess.m, 455 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\测试车牌图像, 0 , 2020-07-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\测试车牌图像\1.jpg, 109992 , 2010-08-31
MATLAB车牌识别[算法对比,GUI]\源码GUI\测试车牌图像\5.jpg, 30660 , 2012-01-16
MATLAB车牌识别[算法对比,GUI]\源码GUI\运行截图.jpg, 870357 , 2020-02-03
MATLAB车牌识别[算法对比,GUI]\源码GUI\运行方式.doc, 344064 , 2020-02-01

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 3Ssearch
    三步搜索法运动估计,用于视频处理的学习和论文(Three-step search motion estimation for video processing of the study and thesis)
    2007-12-19 00:09:28下载
    积分:1
  • hongwaituxiang
    说明:  为了在抑制噪声时尽可能保留图像边缘信息,提出一种自适应各向异性高斯滤波器设计方法. 该方法由独立 强度传播(IDS)模型决定滤波器的长轴尺度,由像素的邻域平滑度决定长短轴的比例,然后根据该处的灰度梯度方 向自适应决定各向异性滤波器的长轴方向. 仿真实验表明,提出的自适应各向异性滤波器具有很强的噪声抑制和 边缘保持能力. (In order to suppress noise, as far as possible to keep the image edge information, an adaptive anisotropic Gaussian filter design methods. The method by the independent strength spread (IDS) model determines the long axis of the filter scale, the pixel neighborhood smoothness determine the ratio of minor axis, and then there' s gray gradient direction of adaptive decision the long axis of anisotropic filter. Simulation results show that the proposed adaptive anisotropic filter has a strong noise suppression and preserve edges.)
    2010-04-19 18:21:00下载
    积分:1
  • duoguangputuxiangpeizhun
    本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景 物在不同波段表现的特征也各不相同等问题,提出了基于互信息相似性测度的 多光谱图像配准算法。(In this paper, multi-spectral image registration between images in different spectral gray there is a big difference, the same scene in different performance characteristics of band varies and so on, based on mutual information similarity measure for multi-spectral image registration algorithm .)
    2009-04-20 11:43:13下载
    积分:1
  • Homomorphic_filter
    同态滤波函数:使用频域处理方法的同态滤波函数,非高斯,巴特沃斯或指数型。对于较黑的图像效果更好(Homomorphic filtering function: the use of frequency domain methods of treatment homomorphic filtering function, non-Gaussian, Butterworth, or index. For more images and better)
    2009-03-18 20:45:46下载
    积分:1
  • mohu_img_enhance
    模糊集图像增强:设计隶属度函数将图像从空间域变换到模糊集域;设计模糊增强算子,在模糊集域对图像进行处理;根据隶属度函数重新将图像从模糊集域变换到空间域。(Fuzzy image enhancement: Designing the membership function of the image from the spatial domain to the fuzzy set domain design fuzzy enhancement operator in fuzzy set domain for image processing membership function according to re-image from the fuzzy set domain to the spatial domain .)
    2021-01-26 23:18:41下载
    积分:1
  • 111
    去雾处理,可以生成深度图和去雾后的图像 用matlab实现(To fog treatment, can generate a depth map and to fog the image after the realization of using matlab)
    2021-05-13 14:30:02下载
    积分:1
  • voxelizer-v1.1
    这个Matlab程序,可以从.OBJ文件中读取三维模型,并转换成单元体表示。同时提供了一个绘图plot函数,来可视化三维物体。 (The Matlab program can be. OBJ file to read three-dimensional model, and converted into cell precursors express. At the same time provides a mapping function plot to visualization of three-dimensional objects.)
    2021-05-13 23:30:02下载
    积分:1
  • Camdemo
    Camshift算法,即"Continuously Adaptive Mean-Shift"算法,是一种自适应的运动跟踪算法。它主要通过视频图像中运动物体的颜色信息来达到跟踪目的。(Camshift algorithm, namely " Continuously Adaptive Mean-Shift" algorithm is an adaptive motion tracking algorithm. It is primarily the color information of the object' s movement through the video images to achieve tracking purposes.)
    2014-01-11 19:45:29下载
    积分:1
  • nmfsc
    基于梯度下降的稀疏约束 NMF 算法(NMFsc),之前pudn上也有类似的,但缺少一个程序,这里面都包括了 (Based on gradient descent sparse constraint NMF algorithm (NMFsc), before the pudn has a similar, but the lack of a program, there are included)
    2020-11-01 20:49:54下载
    积分:1
  • trackinger
    目标跟踪程序,使用matlab编写,采用CV模型,卡尔曼跟踪,有轨迹模拟,给出了跟踪的误差 目标跟踪,采用CV模型,卡尔曼滤波,给出模拟结果和跟踪结果,给出误差分析(Target tracking program, using matlab prepared, using the CV model, Kalman tracking, trajectory simulations have given a tracking error target tracking, using the CV model, Kalman filter, and track the results of the simulation results are given, error analysis is given)
    2021-04-24 17:28:47下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载