[转帖]matlab下gabor滤波算法,可以提取图象纹理特征

suffer

　　%%%%%%%VERSION 1

　　%The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively)

　　%modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively)

　　%described by the following equation

　　%%

　　% 1 -1 x ^ y ^

　　%%% G(x,y) = ---------- * exp ([----{(----) 2+(----) 2}+2*pi*i*(Ux+Vy)])

　　% 2*pi*sx*sy 2 sx sy

　　%% Describtion :

　　%% I : Input image

　　%% Sx & Sy : Variances along x and y-axes respectively

　　%% U & V : Centre frequencies along x and y-axes respectively

　　%% G : The output filter as described above

　　%% gabout : The output filtered image

　　%% Author : Ahmad poursaberi e-mail : a.poursaberi@ece.ut.ac.ir

　　%% Faulty of Engineering, Electrical&Computer Department,Tehran

　　%% University,Iran,June 2004

　　function [G,gabout] = gaborfilter(I,Sx,Sy,U,V);

　　if isa(I,'double')~=1

　　I = double(I);

　　end

　　for x = -fix(Sx):fix(Sx)

　　for y = -fix(Sy):fix(Sy)

　　G(fix(Sx)+x+1,fix(Sy)+y+1) = (1/(2*pi*Sx*Sy))*exp(-.5*((x/Sx)^2+(y/Sy)^2)+2*pi*i*(U*x+V*y));

　　end

　　end

　　Imgabout = conv2(I,double(imag(G)),'same');

　　Regabout = conv2(I,double(real(G)),'same');

　　gabout = uint8(sqrt(Imgabout.*Imgabout + Regabout.*Regabout));

suffer

　　%%%%%%%VERSION 2

　　%%ANOTHER DESCRIBTION OF GABOR FILTER

　　%The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively)

　　%modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively)

　　%described by the following equation

　　%%

　　% -1 x' ^ y' ^

　　%%% G(x,y,theta,f) = exp ([----{(----) 2+(----) 2}])*cos(2*pi*f*x');

　　% 2 sx' sy'

　　%%% x' = x*cos(theta)+y*sin(theta);

　　%%% y' = y*cos(theta)-x*sin(theta);

　　%% Describtion :

　　%% I : Input image

　　%% Sx & Sy : Variances along x and y-axes respectively

　　%% f : The frequency of the sinusoidal function

　　%% theta : The orientation of Gabor filter

　　%% G : The output filter as described above

　　%% gabout : The output filtered image

　　%% Author : Ahmad poursaberi e-mail : a.poursaberi@ece.ut.ac.ir

　　%% Faulty of Engineering, Electrical&Computer Department,Tehran

　　%% University,Iran,June 2004

　　function [G,gabout] = gaborfilter(I,Sx,Sy,f,theta);

　　if isa(I,'double')~=1

　　I = double(I);

　　end

　　for x = -fix(Sx):fix(Sx)

　　for y = -fix(Sy):fix(Sy)

　　xPrime = x * cos(theta) + y * sin(theta);

　　yPrime = y * cos(theta) - x * sin(theta);

　　G(fix(Sx)+x+1,fix(Sy)+y+1) = exp(-.5*((xPrime/Sx)^2+(yPrime/Sy)^2))*cos(2*pi*f*xPrime);

　　end

　　end

　　Imgabout = conv2(I,double(imag(G)),'same');

　　Regabout = conv2(I,double(real(G)),'same');

　　gabout = sqrt(Imgabout.*Imgabout + Regabout.*Regabout);

suffer

　　%%%%%%%VERSION 3

　　%%ANOTHER DESCRIBTION OF GABOR FILTER

　　%The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively)

　　%modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively)

　　%described by the following equation

　　%%

　　% 1 -1 x ^ y ^

　　%%% Gi(x,y) = ---------- * exp ([----{(----) 2+(----) 2}])*Mi(x,y,f);

　　% 2*pi*sx*sy 2 sx sy

　　%%% i =1,2

　　%%% M1(x,y,f) = cos[2*pi*f*sqrt(x^2+y^2)];

　　%%% M2(x,y,f) = cos[2*pi*f*(x*cos(theta) + y*sin(theta)];

　　%% Describtion :

　　%% I : Input image

　　%% Sx & Sy : Variances along x and y-axes respectively

　　%% f : The frequency of the sinusoidal function

　　%% theta : The orientation of Gabor filter

　　%% G1 & G2 : The output filters as described above

　　%% gabout1 & gabout2 : The output filtered images

　　%% Author : Ahmad poursaberi e-mail : a.poursaberi@ece.ut.ac.ir

　　%% Faulty of Engineering, Electrical&Computer Department,Tehran

　　%% University,Iran,June 2004

　　function [G1,G2,gabout1,gabout2] = gaborfilter(I,Sx,Sy,f,theta);

　　if isa(I,'double')~=1

　　I = double(I);

　　end

　　for x = -fix(Sx):fix(Sx)

　　for y = -fix(Sy):fix(Sy)

　　M1 = cos(2*pi*f*sqrt(x^2+y^2));

　　M2 = cos(2*pi*f*(x*cos(theta)+y*sin(theta)));

　　G1(fix(Sx)+x+1,fix(Sy)+y+1) = (1/(2*pi*Sx*Sy)) * exp(-.5*((x/Sx)^2+(y/Sy)^2))*M1;

　　G2(fix(Sx)+x+1,fix(Sy)+y+1) = (1/(2*pi*Sx*Sy)) * exp(-.5*((x/Sx)^2+(y/Sy)^2))*M2;

　　end

　　end

　　Imgabout1 = conv2(I,double(imag(G1)),'same');

　　Regabout1 = conv2(I,double(real(G1)),'same');

　　Imgabout2 = conv2(I,double(imag(G2)),'same');

　　Regabout2 = conv2(I,double(real(G2)),'same');

　　gabout1 = sqrt(Imgabout1.*Imgabout1 + Regabout1.*Regabout1);

　　gabout2 = sqrt(Imgabout2.*Imgabout2 + Regabout2.*Regabout2);

ld1127

　　我怎么不可以运行啊 ,可以举个例子来说明一下吗?

　　麻烦你了

ld1127

我很苯的,您可不可以以一扶图举例一下啊

mubaohong

自己试一下，不是笨不笨的问题，关键是怎么理解

suffer

原帖由 ld1127 于 2006-5-10 09:42 发表
我很苯的,您可不可以以一扶图举例一下啊

注释里非常清楚了，自己好好琢磨一下

Touch

第二个版本里面的参数：
%% Sx & Sy : Variances along x and y-axes respectively
这两个参数都选 1
%% f : The frequency of the sinusoidal function
这个参数选择2，4，8，16
%% theta : The orientation of Gabor filter
这个参数分别是0，45，90，135，180

作为汉字字符图像特征的提取，出来的结果简直惨不忍睹
都没有取到希望方向上的特征
请教一下是为什么呢 ？

fangfei_666

谢谢，刚刚学Gabor，一直看不懂。好好学习去

ChaChing

感觉好像很有趣, 随意找了下! 原始资料是有例子转贴如下
I = imread('cameraman.tif');  
[G,gabout] = gaborfilter1(I,2,4,16,pi/3);  
figure,imshow(uint8(gabout));

转贴有其好处, 但原址或许亦有其他优点(许多人意见)
不过个人外行, 许多不会, 仅列联接有兴趣者或许有用!
http://www.mathworks.com/matlabcentral/fileexchange/5237

boyhailong

怎么都是乱码 啊