【裂缝识别】基于计算机视觉实现道路裂缝识别附matlab代码

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智能优化算法       神经网络预测       雷达通信       无线传感器        电力系统

信号处理              图像处理               路径规划       元胞自动机        无人机 

提出一种基于MATLAB的道路裂缝识别方法,在对道路裂缝图像灰度化的基础上,利用最大类间方差法提取可能存在的道路裂缝,再对图像进行形态学操作,去除图像中的非裂缝区域,最后用凸包对裂缝区域进行标识,得到图像中实际存在的裂缝区域.在采集到的道路裂缝图像的实验结果表明,提出的方法可以准确地标注道路裂缝. ​

function out = imoverlay(in, mask, color)

%IMOVERLAY Create a mask-based image overlay.

%   OUT = IMOVERLAY(IN, MASK, COLOR) takes an input image, IN, and a binary

%   image, MASK, and produces an output image whose pixels in the MASK

%   locations have the specified COLOR.

%

%   IN should be a grayscale or an RGB image of class uint8, uint16, int16,

%   logical, double, or single.  If IN is double or single, it should be in

%   the range [0, 1].  If it is not in that range, you might want to use

%   mat2gray to scale it into that range.

%

%   MASK should be a two-dimensional logical matrix.

%

%   COLOR should be a 1-by-3 vector of values in the range [0, 1].  [0 0 0]

%   is black, and [1 1 1] is white.

%

%   OUT is a uint8 RGB image.

%

%   Examples

%   --------

%   Overlay edge detection result in green over the original image.

%       

%       I = imread('cameraman.tif');

%       bw = edge(I, 'canny');

%       rgb = imoverlay(I, bw, [0 1 0]);

%       imshow(rgb)

%

%   Treating the output of peaks as an image, overlay the values greater than

%   7 in red.  The output of peaks is not in the usual grayscale image range

%   of [0, 1], so use mat2gray to scale it.

%

%       I = peaks;

%       mask = I > 7;

%       rgb = imoverlay(mat2gray(I), mask, [1 0 0]);

%       imshow(rgb, 'InitialMagnification', 'fit')

%   Steven L. Eddins

%   Copyright 2006-2012 The MathWorks, Inc.

% If the user doesn't specify the color, use white.

DEFAULT_COLOR = [1 1 1];

if nargin < 3

    color = DEFAULT_COLOR;

end

% Force the 2nd input to be logical.

mask = (mask ~= 0);

% Make the uint8 the working data class.  The output is also uint8.

in_uint8 = im2uint8(in);

color_uint8 = im2uint8(color);

% Initialize the red, green, and blue output channels.

if ismatrix(in_uint8)

    % Input is grayscale.  Initialize all output channels the same.

    out_red   = in_uint8;

    out_green = in_uint8;

    out_blue  = in_uint8;

else

    % Input is RGB truecolor.

    out_red   = in_uint8(:,:,1);

    out_green = in_uint8(:,:,2);

    out_blue  = in_uint8(:,:,3);

end

% Replace output channel values in the mask locations with the appropriate

% color value.

out_red(mask)   = color_uint8(1);

out_green(mask) = color_uint8(2);

out_blue(mask)  = color_uint8(3);

% Form an RGB truecolor image by concatenating the channel matrices along

% the third dimension.

out = cat(3, out_red, out_green, out_blue);

[1] 康世英, 聂维. 基于MATLAB的道路裂缝识别研究[J]. 电脑知识与技术：学术版, 2020, 16(30):3.

[2] 王博. 基于Matlab图像处理的水泥路面裂缝检测研究[J]. 商洛学院学报, 2014, 28(4):5.

[3] 马文涛, 樊春玲. 基于计算机视觉路面裂缝的识别与测量[J]. 电子测量技术, 2020(019):043.

[4] 史英英. 基于图像处理的路面裂缝识别技术研究[J]. 四川水泥, 2022(11):3.

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