c/c++语言开发共享Matlab实现图像边缘检测

  function output = my_edge(input_img,method)  if size(input_img,3)==3      input_img=rgb2gray(input_img);  end    input_img=im2double(input_img);  sobel_x=[-1,-2,-1;0,0,0;1,2,1];  sobel_y=[-1,0,1;-2,0,2;-1,0,1];  prewitt_x=[-1,-1,-1;0,0,0;1,1,1];  prewitt_y=[-1,0,1;-1,0,1;-1,0,1];    psf=fspecial('gaussian',[5,5],1);  input_img=imfilter(input_img,psf);%高斯低通滤波，平滑图像,但可能会使图像丢失细节  input_img=medfilt2(input_img); %中值滤波消除孤立点  [m,n]=size(input_img);  output=zeros(m,n);  if nargin==2      if strcmp(method,'sobel')          for i=2:m-1              for j=2:n-1                  local_img=input_img(i-1:i+1, j-1:j+1);  %近似边缘检测，加快速度    %output(i,j)=abs(sum(sum(sobel_x.*local_img)))+abs(sum(sum(sobel_x.*local_img)));                  output(i,j)=sqrt(sum(sum(sobel_x.*local_img))^2+sum(sum(sobel_y.*local_img))^2);              end          end      elseif strcmp(method,'prewitt')            for i=2:m-1              for j=2:n-1                  local_img=input_img(i-1:i+1, j-1:j+1);                  output(i,j)=sqrt(sum(sum(prewitt_x.*local_img))^2+sum(sum(prewitt_y.*local_img))^2);              end            end      else          errordlg('maybe you should input sobel or prewitt');      end  else  %如果不输入算子的名称，默认使用roberts算子进行边缘检测      for i=1:m-1          for j=1:n-1              output(i,j)=abs(input_img(i,j)-input_img(i+1,j+1))+ ...                  abs(input_img(i+1,j)-input_img(i,j+1));          end      end  end    output=imadjust(output);%使边缘图像更明显  thresh=graythresh(output);%确定二值化阈值  output=bwmorph(im2bw(output,thresh),'thin',inf);%强化细节  end