指纹图像特征提取与matlab实现

%指纹特征点(细节点)提取 clc,clear,close all %% Read Input Image binary_image=im2bw(imread('2.bmp')); % figure;imshow(binary_image);title('Input image'); %% Small region is taken to show output clear binary_image = binary_image(30:460,25:350); %截取其中一部分 figure;imshow(binary_image);title('Input image'); %% Thinning thin_image=~bwmorph(binary_image,'thin',Inf); figure;imshow(thin_image);title('Thinned Image'); % load('ridge.mat') % load('bifurcation.mat') % hold on % plot(ridge_y,ridge_x,'r*') % plot(bifurcation_y,bifurcation_x,'b.','markersize',8) %% Minutiae extraction s=size(thin_image); N=3;%window size n=(N-1)/2; r=s(1)+2*n; c=s(2)+2*n; double temp(r,c); temp=zeros(r,c);bifurcation=zeros(r,c);ridge=zeros(r,c); % ‘0’ 表示全黑色 temp((n+1):(end-n),(n+1):(end-n))=thin_image(:,:); outImg=zeros(r,c,3); % For Display outImg(:,:,1) = temp .* 255; outImg(:,:,2) = temp .* 255; outImg(:,:,3) = temp .* 255; for x=(n+1+10):(s(1)+n-10) for y=(n+1+10):(s(2)+n-10) e=1; for k=x-n:x+n f=1; for l=y-n:y+n mat(e,f)=temp(k,l); f=f+1; end e=e+1; end; if(mat(2,2)==0) ridge(x,y)=sum(sum(~mat)); bifurcation(x,y)=sum(sum(~mat)); end end; end; hold on %% 纹数 [ridge_x ridge_y]=find(ridge==2); plot(ridge_y,ridge_x,'r*') %% 分叉点 [bifurcation_x bifurcation_y]=find(bifurcation==4); plot(bifurcation_y,bifurcation_x,'b.','markersize',8) save ridge.mat ridge_x ridge_y save bifurcation.mat bifurcation_x bifurcation_y