MATLAB车牌定位实现系统.zip

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MATLAB车牌定位实现系统/

MATLAB车牌定位实现系统/1.jpg

4.83KB

MATLAB车牌定位实现系统/finddomain.m

1.21KB

MATLAB车牌定位实现系统/main.m

2.67KB

MATLAB车牌定位实现系统/mainfc.p

202B

MATLAB车牌定位实现系统/removeLargeArea.m

2.75KB

MATLAB车牌定位实现系统/二值图结果.bmp

1.92KB

资源内容介绍

Matlab车牌识别系统是一个使用Matlab编程语言开发的程序，用来识别汽车车牌上的字符和数字。该系统可以通过读取车牌图像，并使用图像处理、模式识别和机器学习算法来识别和解析车牌上的字符和数字。以下是一个基本的车牌识别系统的工作流程：1. 图像预处理：对车牌图像进行预处理，例如去噪、增强对比度、调整亮度等。2. 车牌定位：使用图像处理算法定位车牌在图像中的位置。3. 字符分割：将车牌图像分割成单个字符，以便对每个字符进行识别。4. 字符识别：使用模式识别或机器学习算法对每个字符进行识别和分类。5. 车牌解析：将识别出的字符组合成完整的车牌号码。6. 输出结果：将识别结果输出到屏幕或保存到文件中。在开发Matlab车牌识别系统时，可以使用Matlab的图像处理工具箱、模式识别工具箱和机器学习工具箱来实现各种功能。此外，还可以使用深度学习模型如卷积神经网络（CNN）来提高字符识别的准确性。可以使用现有的开源深度学习框架（如TensorFlow或PyTorch）来训练和部署深度学习模型，并将其与Matlab集成。总之，Matlab车牌识别系统是一个使用Matl

function bw2 = removeLargeArea(varargin)%BWAREAOPEN Remove small objects from binary image.% BW2 = BWAREAOPEN(BW,P) removes from a binary image all connected% components (objects) that have fewer than P pixels, producing another% binary image BW2. This operation is known as an area opening. The% default connectivity is 8 for two dimensions, 26 for three dimensions,% and CONNDEF(NDIMS(BW),'maximal') for higher dimensions. %% BW2 = BWAREAOPEN(BW,P,CONN) specifies the desired connectivity. CONN% may have the following scalar values: %% 4 two-dimensional four-connected neighborhood% 8 two-dimensional eight-connected neighborhood% 6 three-dimensional six-connected neighborhood% 18 three-dimensional 18-connected neighborhood% 26 three-dimensional 26-connected neighborhood%% Connectivity may be defined in a more general way for any dimension by% using for CONN a 3-by-3-by- ... -by-3 matrix of 0s and 1s. The% 1-valued elements define neighborhood locations relative to the center% element of CONN. CONN must be symmetric about its center element.%% Class Support% -------------% BW can be a logical or numeric array of any dimension, and it must be% nonsparse.%% BW2 is logical.%% Example% -------% Remove all objects in the image text.png containing fewer than 50% pixels.%% BW = imread('text.png');% BW2 = bwareaopen(BW,50);% imshow(BW);% figure, imshow(BW2)%% See also BWCONNCOMP, CONNDEF, REGIONPROPS.% Copyright 1993-2011 The MathWorks, Inc.% $Revision: 1.10.4.9 $ $Date: 2011/11/09 16:48:52 $% Input/output specs% ------------------% BW: N-D real full matrix% any numeric class% sparse not allowed% anything that's not logical is converted first using% bw = BW ~= 0% Empty ok% Inf's ok, treated as 1% NaN's ok, treated as 1%% P: double scalar% nonnegative integer%% CONN: connectivity%% BW2: logical, same size as BW% contains only 0s and 1s.[bw,p,conn] = parse_inputs(varargin{:});CC = bwconncomp(bw,conn);area = cellfun(@numel, CC.PixelIdxList);idxToKeep = CC.PixelIdxList(area <= p);idxToKeep = vertcat(idxToKeep{:});bw2 = false(size(bw));bw2(idxToKeep) = true;%%%%%% parse_inputs%%%function [bw,p,conn] = parse_inputs(varargin)narginchk(2,3)bw = varargin{1};validateattributes(bw,{'numeric' 'logical'},{'nonsparse'},mfilename,'BW',1);if ~islogical(bw) bw = bw ~= 0;endp = varargin{2};validateattributes(p,{'double'},{'scalar' 'integer' 'nonnegative'},... mfilename,'P',2);if (nargin >= 3) conn = varargin{3};else conn = conndef(ndims(bw),'maximal');endiptcheckconn(conn,mfilename,'CONN',3)

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MATLAB车牌定位实现系统.zip

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