histDist.zip_carem78_matlab HistDist_site:www.pudn.com_彩色图像分类_直方

% %I1hsv=rgb2hsv(I1); % %I1hsv(:,:,1) %量化成16级 % %u=1:16*16*4 % clear,clf % I1=imread('render020.jpg');I2=imread('ceshi.jpg'); % imshow(I1);figure(4),imshow(I2); % I1=double(I1);%若不先转为double，除32无法准确转换到8个区间内 % I18=floor(I1./32);%convert to 8 zones; % I2=double(I2);I28=floor(I2./32); % figure(1),hold on % rect=getrect; % rect=floor(rect); % x1=rect(1); % x2=x1+rect(3); % y1=rect(2); % y2=y1+rect(4); % yc=[floor(rect(4)/2) floor(rect(3)/2)];%目标区域中心 % xprimes=[x1 x2 x2 x1 x1]; % yprimes=[y1 y1 y2 y2 y1]; % hold on % plot(xprimes,yprimes,'r','linewidth',2); % %plot(x1+yc(1),y1+yc(2),'g*');%目标区域中心 % hold off % figure(4); % hold on % plot(xprimes,yprimes,'r','linewidth',2); % %plot(x1+yc(1),y1+yc(2),'g*');%目标区域中心 % hold off % % tmp=I18(y1:y2,x1:x2,:);tmp2=I28(y1:y2,x1:x2,:); % [nr,nc,nb]=size(tmp); % % for i=0:511 % u(i+1,1)=mod(floor(i/64),8); % u(i+1,2)=mod(floor(i/8),8); % u(i+1,3)=mod(i,8); % end % % % q=zeros(1,512); % % for i=1:512 % % for r=1:nr % % for c=1:nc % % q(i)=q(i)+(tmp(r,c,1)==u(i,1) & tmp(r,c,2)==u(i,2) & tmp(r,c,3)==u(i,3)); % % end % % end % % end % % h1=sqrt((rect(4)/2)^2+(rect(3)/2)^2);%h为跟踪窗宽（包括长度ch和宽度cl） % %h=[rect(4)/2,rect(3)/2]; % % sumkt=0; % for r=1:(nr-1) % for c=1:(nc-1) % x((r-1)*nc+c,1)=r; % x((r-1)*nc+c,2)=c; % t=((x((r-1)*nc+c,1)-yc(1))/h1)^2+((x((r-1)*nc+c,2)-yc(2))/h1)^2; % %t=sum(((x((r-1)*nc+c,:)-yc)/h)^2);%%%%行和列对应的么？？？？？ % if t<=1 % kt=1-t^2; % else % kt=0; % end % sumkt=sumkt+kt; % end % end % C=1/sumkt; % % for i=1:512 % sumkt=0;sumkt2=0; % for r=1:(nr-1) % for c=1:(nc-1) % x((r-1)*nc+c,1)=r; % x((r-1)*nc+c,2)=c; % t=((x((r-1)*nc+c,1)-yc(1))/h1)^2+((x((r-1)*nc+c,2)-yc(2))/h1)^2; % %t=sum(((x((r-1)*nc+c)-yc)/h)^2); % if t<=1 % kt=1-t^2; % else % kt=0; % end % sumkt=sumkt+kt*(tmp(r,c,1)==u(i,1) & tmp(r,c,2)==u(i,2) & tmp(r,c,3)==u(i,3)); % sumkt2=sumkt2+kt*(tmp2(r,c,1)==u(i,1) & tmp2(r,c,2)==u(i,2) & tmp2(r,c,3)==u(i,3)); % end % end % q(i)=C*sumkt; % q2(i)=C*sumkt2; % end % figure(2); % %subplot(1,2,1),plot(1:512,q,'r','linewidth',2); % %subplot(1,2,2), % subplot(1,2,1),bar(q); % subplot(1,2,2),bar(q2); % % rou=sum(sqrt(q.*q2));%计算巴氏距离 % d=sqrt(1-rou) %%%3维柱状图显示图片区域颜色分布情况 I=imread('render020.jpg'); [tmp1 rect]=imcrop(I); [nr1,nc1,nb1]=size(tmp1); tmp1=double(tmp1); tmp1=floor(tmp1/32); x1=rect(1);x2=x1+rect(3);y1=rect(2);y2=y1+rect(4); xprimes=[x1,x2,x2,x1,x1];yprimes=[y1,y1,y2,y2,y1]; hold on plot(xprimes,yprimes,'r','linewidth',2); for i=0:511 u(i+1,1)=mod(floor(i/64),8); u(i+1,2)=mod(floor(i/8),8); u(i+1,3)=mod(i,8); end yc=[floor(rect(4)/2) floor(rect(3)/2)];%目标区域中心 h1=sqrt((rect(4)/2)^2+(rect(3)/2)^2);%h为跟踪窗宽（包括长度ch和宽度cl） for r=1:nr1 for c=1:nc1 x((r-1)*nc1+c,1)=r; x((r-1)*nc1+c,2)=c; t=((x((r-1)*nc1+c,1)-yc(1))/h1)^2+((x((r-1)*nc1+c,2)-yc(2))/h1)^2; %t=sum(((x((r-1)*nc+c,:)-yc)/h)^2);%%%%行和列对应的么？？？？？ if t<=1 kt(r,c)=1-t^2; else kt(r,c)=0; end end end for i=1:512 for r=1:nr1 for c=1:nc1 if (tmp1(r,c,1)==u(i,1)&tmp1(r,c,2)==u(i,2)&tmp1(r,c,3)==u(i,3)) f(r,c)=i*kt(r,c); end end end end figure(2); bar3(f) % clear,clf % I1=imread('render020.jpg');I2=imread('ceshi.jpg'); % imshow(I1);figure(4),imshow(I2); % I1=double(I1);%若不先转为double，除32无法准确转换到8个区间内 % I18=floor(I1./32);%convert to 8 zones; % I2=double(I2);I28=floor(I2./32); % figure(1),hold on % rect=getrect; % rect=floor(rect); % x1=rect(1); % x2=x1+rect(3); % y1=rect(2); % y2=y1+rect(4); % yc=[floor(rect(4)/2) floor(rect(3)/2)];%目标区域中心 % xprimes=[x1 x2 x2 x1 x1]; % yprimes=[y1 y1 y2 y2 y1]; % hold on % plot(xprimes,yprimes,'r','linewidth',2); % hold off % figure(4); % hold on % plot(xprimes,yprimes,'r','linewidth',2); % hold off % % tmp=I18(y1:y2,x1:x2,:);tmp2=I28(y1:y2,x1:x2,:); % [nr,nc,nb]=size(tmp); % % h1=sqrt((rect(4)/2)^2+(rect(3)/2)^2);%h为跟踪窗宽（包括长度ch和宽度cl） % % sumkt=0; % for r=1:(nr-1) % for c=1:(nc-1) % x((r-1)*nc+c,1)=r; % x((r-1)*nc+c,2)=c; % t=((x((r-1)*nc+c,1)-yc(1))/h1)^2+((x((r-1)*nc+c,2)-yc(2))/h1)^2; % if t<=1 % kt=1-t^2; % else % kt=0; % end % sumkt=sumkt+kt; % end % end % C=1/sumkt; % % for i=1:8 % sumktr=0;sumkt2r=0;sumktg=0;sumkt2g=0;sumktb=0;sumkt2b=0; % for r=1:(nr-1) % for c=1:(nc-1) % x((r-1)*nc+c,1)=r; % x((r-1)*nc+c,2)=c; % t=((x((r-1)*nc+c,1)-yc(1))/h1)^2+((x((r-1)*nc+c,2)-yc(2))/h1)^2; % if t<=1 % kt=1-t^2; % else % kt=0; % end % sumktr=sumktr+kt*(tmp(r,c,1)==i); % sumktg=sumktg+kt*(tmp(r,c,2)==i); % sumktb=sumktb+kt*(tmp(r,c,3)==i); % sumkt2r=sumkt2r+kt*(tmp2(r,c,1)==i); % sumkt2g=sumkt2g+kt*(tmp2(r,c,2)==i); % sumkt2b=sumkt2b+kt*(tmp2(r,c,3)==i); % end % end % qr(i)=C*sumktr; % qg(i)=C*sumktg; % qb(i)=C*sumktb; % q2r(i)=C*sumkt2r; % q2g(i)=C*sumkt2g; % q2b(i)=C*sumkt2b; % end % figure(2); % subplot(2,3,1),bar(qr);subplot(2,3,2),bar(qg);subplot(2,3,3),bar(qb); % subplot(2,3,4),bar(q2r);subplot(2,3,5),bar(q2g);subplot(2,3,6),bar(q2b); % % rour=sum(sqrt(qr.*q2r));%计算巴氏距离 % roug=sum(sqrt(qg.*q2g)); % roub=sum(sqrt(qb.*q2b)); % dr=sqrt(1-rour) % dg=sqrt(1-roug) % db=sqrt(1-roub) %核密度估计求解的例子： % xdata = normrnd(10,1,5000,1); % [fk,xk,h] = ksdensity(xdata); % [f,xi] = ecdf(xdata); % ecdfhist(f,xi,range(xdata)/h); % hold on % plot(xk,fk,'r','linewidth',2); % fun = @(x,xdata)-ksdensity(xdata,x); % xfz = fminsearch(fun,mean(xdata),[],xdata); % plot(xfz,ksdensity(xdata,xfz),'g*','markersize',15);