指纹识别的matlab代码

function thin=yuchuli(abc) imshow(abc);title('原图像'); A=imread(abc); I=rgb2gray(A); I=double(I); % 归一化 M=0;var=0; %m=299;n=258;%图像的平均值和方差开始进行初始化 [m,n]=size(I); for x=1:m for y=1:n M=M+I(x,y); end end M1=M/(m*n);%计算图像的平均值 for x=1:m for y=1:n var=var+(I(x,y)-M1).^2;%计算图像的方差 end end var1=var/(m*n); for x=1:m for y=1:n if I(x,y)>=M1 I(x,y)=150+sqrt(2000*(I(x,y)-M1)/var1);%处理后的图像均值 else I(x,y)=150-sqrt(2000*(M1-I(x,y))/var1);%处理后的图像方差 end end end figure, imshow(uint8(I));title('归一化');%显示归一化后的图像 % 分割 M =3; %3*3 H = m/M; L= n/M; aveg1=zeros(H,L); var1=zeros(H,L); % 计算每一块的平均值 for x=1:H; for y=1:L; aveg=0;var=0; for i=1:M; for j=1:M; aveg=I(i+(x-1)*M,j+(y-1)*M)+aveg; end end aveg1(x,y)=aveg/(M*M); % 计算每一块的方差值 for i=1:M; for j=1:M; var=(I(i+(x-1)*M,j+(y-1)*M)-aveg1(x,y)).^2+var; end end var1(x,y)=var/(M*M); end end Gmean=0;Vmean=0; for x=1:H for y=1:L Gmean=Gmean+aveg1(x,y); Vmean=Vmean+var1(x,y); end end Gmean1=Gmean/(H*L);%所有块的平均值 Vmean1=Vmean/(H*L);%所有块的方差 gtemp=0;gtotle=0;vtotle=0;vtemp=0; for x=1:H for y=1:L if Gmean1>aveg1(x,y) gtemp=gtemp+1; gtotle=gtotle+aveg1(x,y); end if Vmean1<var1(x,y) vtemp=vtemp+1; vtotle=vtotle+var1(x,y); end end end G1=gtotle/gtemp;V1=vtotle/vtemp; gtemp1=0;gtotle1=0;vtotle1=0;vtemp1=0; for x=1:H for y=1:L if G1<aveg1(x,y) gtemp1=gtemp1-1; gtotle1=gtotle1+aveg1(x,y); end if 0<var1(x,y)<V1 vtemp1=vtemp1+1; vtotle1=vtotle1+var1(x,y); end end end G2=gtotle1/gtemp1;V2=vtotle1/vtemp1; e=zeros(H,L); for x=1:H for y=1:L if aveg1(x,y)>G2 && var1(x,y)<V2%如果M>M1且Var<Var1，则认为背景 e(x,y)=1; end %如果M<=M1且Var>=Var1，则认为前景，否则待定 if aveg1(x,y)< G1-100 && var1(x,y)< V2 e(x,y)=1; end end end for x=2:H-1 for y=2:L-1 if e(x,y)==1 if e(x-1,y) + e(x-1,y+1) +e(x,y+1) + e(x+1,y+1) + e(x+1,y) + e(x+1,y-1) + e(x,y-1) + e(x-1,y-1) <=4 e(x,y)=0; end end end end Icc = ones(m,n); for x=1:H for y=1:L if e(x,y)==1 for i=1:M for j=1:M I(i+(x-1)*M,j+(y-1)*M)=G1; Icc(i+(x-1)*M,j+(y-1)*M)=0; end end end end end figure, imshow(Icc);title('分割'); %二值化? temp=(1/9)*[1 1 1;1 1 1;1 1 1];%模板系数 均值滤波 Im=double(I); In=zeros(m,n);% 创建一个全0的二维数组，m行n列 for a=2:m-1; for b=2:n-1; In(a,b)=Im(a-1,b-1)*temp(1,1)+Im(a-1,b)*temp(1,2)+Im(a-1,b+1)*temp(1,3)+Im(a,b-1)*temp(2,1)+Im(a,b)*temp(2,2)+Im(a,b+1)*temp(2,3)+Im(a+1,b-1)*temp(3,1)+Im(a+1,b)*temp(3,2)+Im(a+1,b+1)*temp(3,3); end end I=In; Im=zeros(m,n);% 创建一个全0的二维数组，m行n列 for x=5:m-5; for y=5:n-5; %分别计算8个方向上的经过处理后的灰度值 sum1=I(x,y-4)+I(x,y-2)+I(x,y+2)+I(x,y+4); sum2=I(x-2,y+4)+I(x-1,y+2)+I(x+1,y-2)+I(x+2,y-4); sum3=I(x-2,y+2)+I(x-4,y+4)+I(x+2,y-2)+I(x+4,y-4); sum4=I(x-2,y+1)+I(x-4,y+2)+I(x+2,y-1)+I(x+4,y-2); sum5=I(x-2,y)+I(x-4,y)+I(x+2,y)+I(x+4,y); sum6=I(x-4,y-2)+I(x-2,y-1)+I(x+2,y+1)+I(x+4,y+2); sum7=I(x-4,y-4)+I(x-2,y-2)+I(x+2,y+2)+I(x+4,y+4); sum8=I(x-2,y-4)+I(x-1,y-2)+I(x+1,y+2)+I(x+2,y+4); sumi=[sum1,sum2,sum3,sum4,sum5,sum6,sum7,sum8]; summax=max(sumi);%经过处理后的灰度值，找到他们中最大值 summin=min(sumi);%经过处理后的灰度值，找到他们中最小值 summ=sum(sumi); b=summ/8;%若满足(summax+summin+ 4*I(x,y))> (3*summ/8) if (summax+summin+ 4*I(x,y))> (3*summ/8) sumf = summin;%则该像素点的脊线方向为summin else sumf = summax;%否则为summax end if sumf > b%确定完方向后就根据该向场对图像进行二值化 Im(x,y)=128; else Im(x,y)=255; end end end for i=1:m for j =1:n Icc(i,j)=Icc(i,j)*Im(i,j); end end for i=1:m for j =1:n if (Icc(i,j)==128) Icc(i,j)=0; else Icc(i,j)=1; end; end end figure,imshow(double(Icc));title('二值化'); u=Icc; [m,n]=size(u); %去除空洞和毛刺 for x=2:m-1 for y=2:n-1 if u(x,y)==0 if u(x,y-1)+u(x-1,y)+u(x,y+1)+u(x+1,y)>=3 u(x,y)=1; end else u(x,y)=u(x,y); end end end figure,imshow(u) title('去除毛刺') for a=2:m-1 for b=2:n-1 if u(a,b)==1 if abs(u(a,b+1)-u(a-1,b+1))+abs(u(a-1,b+1)-u(a-1,b))+abs(u(a-1,b)-u(a-1,b-1))+abs(u(a-1,b-1)-u(a,b-1))+abs(u(a,b-1)-u(a+1,b-1))+abs(u(a+1,b-1)-u(a+1,b))+abs(u(a+1,b)-u(a+1,b+1))+abs(u(a+1,b+1)-u(a,b+1))~=1%寻找端点 if (u(a,b+1)+u(a-1,b+1)+u(a-1,b))*(u(a,b-1)+u(a+1,b-1)+u(a+1,b))+(u(a-1,b)+u(a-1,b-1)+u(a,b-1))*(u(a+1,b)+u(a+1,b+1)+u(a,b+1))==0 %去除空洞和毛刺 u(a,b)=0; end end end end end figure,imshow(u) title('去除空洞') v=~u; se=strel('square',3);%创建形态学结构元素 fo=imopen(v,se);%对图像进行开操作和闭操作 v=imclose(fo,se); %对图像进行开操作和闭操作 w=bwmorph(v,'thin',Inf);%对图像进行细化 thin=w; figure,imshow(w) title('细化图')