使用 houstransform 和小波变换的眼检测 检测的眼睛使用使用自适应处理技术的小波变换和 hough 检测算法.zip

%By leaper RGB = imread('123.jpg'); imshow(RGB); text(15,15,'Estimate radius of iris',... 'FontWeight','bold','Color','y'); I = rgb2gray(RGB); threshold = graythresh(I); BW = im2bw(I,threshold); %imshow(BW) dim = size(BW); col = round(dim(2)/2)-95; row = find(BW(:,col), 1); connectivity = 4; num_points = 300; contour = bwtraceboundary(BW, [row, col], 'N', connectivity, num_points); %imshow(RGB); %hold on; mask = bsxfun(@plus, ((1:552) - 249.5083).^2, (transpose(1:298) - 125.3709).^2) < (41)^2; count=1; for xs=1:552 for ys=1:298 if (mask(ys,xs)==1) xnews(count)=xs; ynews(count)=ys; count=count+1; end end end mask1 = bsxfun(@plus, ((1:552) -2.475082563312659e+02).^2, (transpose(1:298) - 1.273709462474379e+02).^2) < (1.204731808283926e+02)^2; count1=1; for xs1=1:552 for ys1=1:298 if (mask1(ys1,xs1)==0) xnews1(count1)=xs1; ynews1(count1)=ys1; count1=count1+1; end end end for q1=1:(count1-1) I(ynews1(q1),xnews1(q1))=0; end for q=1:(count-1) I(ynews(q),xnews(q))=0; end imshow(I) % hold on; BW1 = im2bw(I,0.3); [B,L,N] = bwboundaries(BW1); % for k=1:length(B) % boundary = B{k}; % if(k > N) % plot(boundary(:,2),� boundary(:,1),'b','LineWidth',4); % % end % end %plot(contour(:,2),contour(:,1),'g','LineWidth',6); x = contour(:,2); y = contour(:,1); % solve for parameters a, b, and c in the least-squares sense by % using the backslash operator abc = [x y ones(length(x),1)] \ -(x.^2+y.^2); a = abc(1); b = abc(2); c = abc(3); % calculate the location of the center and the radius xc = -a/2; yc = -b/2; radius = sqrt((xc^2+yc^2)-c) % display the calculated center %plot(xc,yc,'yx','LineWidth',2); % plot the entire circle theta = 0:0.01:2*pi; % use parametric representation of the circle to obtain coordinates % of points on the circle Xfit = radius*cos(theta) + xc; Yfit = radius*sin(theta) + yc; %plot(Xfit, Yfit,'b','LineWidth',4); % plot(Xfit, Yfit); message = sprintf('Radius of iris is %2.3f pixels', radius); text(15,15,message,'Color','y','FontWeight','bold');