ocl.rar_ocl_图像质量_指纹质量_方向确定度

% OCL Compute the orientation certainity level of fingerprint image. % % Function to assess the quality of fingerprint image % % Usage: [score] = ocl(f, blocksize); % % Argument: im - Fingerprint image to be assessed. % blocksize - the scale of the block which will be assessed. % % Returns: score - the score of the fingerprint image being assessed. % % % Jerry Zhao & Li Xiutao % School of Computer Science & Software Engineering % Si Chuan University % http://www.qijunzhao.org % % January 2013 function [ocl] = ocl(f, blocksize) if ~(nargin == 1 || nargin == 2) error('Usage: [score] = ocl(im, blocksize)'); end ocl = 0; f=double(f); [m n]=size(f); row=m-mod(m,blocksize); column=n-mod(n,blocksize); oclPerBlock=zeros(row/blocksize,column/blocksize)+100; %numberOfBlock = (row/32)*(column/32); n=0; NO =0;%记录可计算的block的数目。 for i=1:blocksize:row-1 for j=1:blocksize:column-1 M = f(i:i+blocksize-1,j:j+blocksize-1); [Fx, Fy] = gradient(M); C = [0,0;0,0]; for h=1:blocksize C = C+[Fx(h);Fy(h)]*[Fx(h),Fy(h)]; end C = C/(32*32); a = C(1); b = C(4); c = C(2); lmin = ((a+b)-sqrt((a-b)^2 + 4*c^2))/2; lmax = ((a+b)+sqrt((a-b)^2 + 4*c^2))/2; n=n+1; if ~(lmax == 0) NO = NO+1; ocl = lmin/lmax; oclPerBlock(n) = ocl; end end end ocl = ocl/NO; n=0; f = cat(3,f,f,f); for i=1:blocksize:row-1 for j=1:blocksize:column-1 f =drawRect(f,[i,j],[32,32],'r',1); end end f = uint8(drawRect(f,[0,0],[32,32],'r',1)); imshow(f) hold on for h=1:(row/blocksize) for k=1:(column/blocksize) n = n+1; text((k-1)*blocksize+blocksize/2,(h-1)*blocksize+blocksize/2,num2str(oclPerBlock(n)),'color','r'); end end