classify_img2.m

Information Fusion of Flash and Non-Flash Images (Project)

function [res_img] = classify_img2(rgb_img, t_inds,tol);
%Uses multiple cubes for background
%convert to YCbCr- this has less covariance
ycc_img = double(rgb2ycbcr(rgb_img));
[M N P] = size(rgb_img);
Y_img = reshape(scaleData(ycc_img(:,:,1),0,1),M*N,1);
CB_img = reshape(scaleData(ycc_img(:,:,2),0,1),M*N,1);
CR_img = reshape(scaleData(ycc_img(:,:,3),0,1),M*N,1);

tdata = [Y_img(t_inds), CB_img(t_inds), CR_img(t_inds)];
img_data = [Y_img, CB_img, CR_img];

%train..
tdata1 = randomize_tdata(tdata);
tdata2 = randomize_tdata(tdata);
tdata3 = randomize_tdata(tdata);

tcubes1 = getCubes(tdata1,tol);
tcubes2 = getCubes(tdata2,tol);
tcubes3 = getCubes(tdata3,tol);

%now classify
resvec1 = fuzzy_classify2(img_data,tcubes1,tol);
resvec1 = resvec1 + fuzzy_classify2(img_data,tcubes2,tol);
resvec1 = resvec1 + fuzzy_classify2(img_data,tcubes3,tol);

resvec = (resvec1 > 1);
figure(5);
imagesc(reshape(resvec1,M,N));
colormap(gray);
%results(t_inds) = 2;
res_img1 = reshape(resvec,M,N);
res_img = medfilt2(res_img1);