基于轮廓提取的多边形近似匹配算法 matlaB

 %script FILE FOR CONTOUR FOLLOWING IN A BINARY IMAGE
%AUTHOR : RAJJAN SINGH THAKUR （VIT UNIVERSITY）
%DATE :14/2/09
function [cntcnt2area1area2]= mobanpipei（）

% for（i=1:100）
%     for（j=1:100）
% 
%         a（ij）=0;
%     end
% end
%  c=roipoly（a）;
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%                     图像轮廓提取                       %       
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%%a=imread（‘000.bmp‘）;
%%c=im2bw（rgb2gray（a）254/255）;
%imshow（c）;
%%t=0;
%s=input（‘press l to select row from left and r to select row from right \n enter the alphabet within  single quote \n press enter after each result to continue‘）;
%switch（s）
%case ‘l‘
    %%for（i=1:size（c1））;
       %% for（j=1:size（c2））;
            %%if（c（ij）==0）
               %% t=t+1;
               %% col2（t:）=[ij];
               %% break;
           %% end
       %% end
    %%end
    
%case ‘r‘
   % for（i=1:size（c1））;
    %    for（j=size（c2）:-1:1）;
  %          if（c（ij）==1）
  %              t=t+1;
   %             col2（t:）=[ij];
   %             break;
   %         end
   %     end
  %  end
%otherwise 
   % []
%end

%FUNCTION TO COMPUTE THE CONTOUR IN BINARY IMAGE
%%[k1mn]=contour_b_trial_2（ccol2（11）col2（12））;
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%                     图像轮廓提取                       %       
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%                     多边形近似                        %       
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%%k=im2bw（k10）;
k=openpic（）;

h=boundaries（k4‘cw‘）; 
h=h{1};
[M1N1]=size（k）;
xmin=min（h（:1））;
ymin=min（h（:2））;
bim=bound2im（hM1N1xminymin）;
[xy]=minperpoly（k3）;
b2=connectpoly（xy）;
B2=bound2im（b2M1N1xminymin）;
B3=zeros（size（B21）size（B22））;
for i=1:size（B21）
    for j=1:size（B22）
        if B2（ij）==0
            B3（ij）=0;
        end
        if B2（ij）==1
            B3（ij）=255;
        end
    end
end
B3=mat2gray（B3）;
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%                     多边形近似                        %       
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%                  Harris角点检测                       %       
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[coutmarked_imgcd] = cpda（B3）;
%%ori_im2=B3;  
%%fx = [5 0 -5;8 0 -8;5 0 -5];          % % la gaucienne，ver axe x
%%Ix = filter2（fxori_im2）;              % la convolution vers axe x
%%fy = [5 8 5;0 0 0;-5 -8 -5];          % la gaucienne，ver axe y
%%Iy = filter2（fyori_im2）;              % la convolution vers axe y
%%Ix2 = Ix.^2;
%%Iy2 = Iy.^2;
%%Ixy = Ix.*Iy;
%%clear Ix;
%%clear Iy;

%%h= fspecial（‘gaussian‘[3 3]2）;      % générer une fonction gaussienne，sigma=2

%%Ix2 = filter2（hIx2）