clc; clear all; close all; tic; format LONG I = imread('E:\8th sem project\numbers and alphabets images database\two.jpg'); bwim1=adaptivethreshold(I,11,0.03,0); % adaptive thresholding of the image imwrite(bwim1,'new.png','bitdepth',1); I5 = imread('new.png'); %imtool(I) %b = bwtraceboundary(I,[273, 13],'S') %[x,y] = bwboundaries(I,8) [x,y] = find(I5 == 0); xr = round(x); yr = round(y); %l = length(x); l = 11; xc = sum(x)/l; yc = sum(y)/l; % Resizing of the image. % I6 = imresize(I,[120,120]); % imwrite(I6,'neww.jpg'); % I7 = imread('neww.jpg'); grayi = rgb2gray(I); for t = 1:l r(t) = sqrt((x(t) - xc)^2 + (y(t) - yc)^2); idx(t) = sub2ind(size(grayi),xr(t),yr(t)); g(t) = grayi(idx(t)); %g(t) = grayi(xr(t),yr(t)); phi(t) = double(r(t)*g(t));
end
for n = 1:l-1 b = 0; for t = 1:l b(t) = (phi(t).*exp(-2*j*pi*n*(t)/l)); end a(n) = sum(b)/l; a(l) = sum(r); s(n) = abs(a(n))/a(l); end S = s(1:10);
len = 0;
s1 = 0;
x1 = 0;
y1 = 0;
i =2;
minm = 0;
mi = 1;
srcFiles2 = dir('E:\8th sem project\Adaptive thresholding\Attachments_201555\*.png');
for k = 1:length(srcFiles2)
filename = strcat('E:\8th sem project\Adaptive thresholding\Attachments_201555\',srcFiles2(k).name);
I1 = imread(filename);
[x1,y1] = find(I1 == 0);
xr1 = round(x1);
yr1 = round(y1);
len = 11;
xc1 = sum(x1)/len;
yc1 = sum(y1)/len;
srcFiles3 = dir('E:\8th sem project\Adaptive thresholding\ORIGINAL\*.jpg'); for k1 = 1:length(srcFiles3) filenames = strcat('E:\8th sem project\Adaptive thresholding\ORIGINAL\',srcFiles3(k1).name); I51 = imread(filenames); grayi1 = rgb2gray(I51);
for t1 = 1:len r1(t1) = sqrt((x1(t1) - xc1)^2 + (y1(t1) - yc1)^2); idx1 = sub2ind(size(grayi1),xr1(t1),yr1(t1)); g1(t1) = grayi1(idx1); phi1(t1) = double(r1(t1)*g1(t1));
end
for n1 = 1:len-1 b1 = 0; for t1 = 1:len b1(t1) = (phi1(t1).*exp(-2*j*pi*n1*(t1)/l)); end a1(n1) = sum(b1)/len; a1(len) = sum(r1);%supposed to be a(0) but matlab doesn't allow 0 to be as the index value. %a(n) = [sum(phi(1:l)*exp(-2*j*3.14*n*(1:l)/l))]/l; s1(n) = abs(a1(n1))/a1(len); end S1 = s1(1:10);
D(k) = sqrt(sum((S - S1).^2))
if (k==1)
minm = D(k);
else
m(i) = D(k);
end
if (k>1)
if(m(i) < minm)
minm = m(i);
mi = k;
end
end
i = i +1;
a1 = 0;
end
end
minimum = min(D)
disp(srcFiles2(mi).name)
toc
This is my entire code.
But it is incorrectly matching.
For one as the test image input, i got six as the output.
Please help me improvise this.
I have 6 images per gesture in my database and saved after adaptive thresholding.
function bw=adaptivethreshold(IM,ws,C,tm) %ADAPTIVETHRESHOLD An adaptive thresholding algorithm that seperates the %foreground from the background with nonuniform illumination. % bw=adaptivethreshold(IM,ws,C) outputs a binary image bw with the local % threshold mean-C or median-C to the image IM. % ws is the local window size. % tm is 0 or 1, a switch between mean and median. tm=0 mean(default); tm=1 median. % % Contributed by Guanglei Xiong (<mailto:xgl99@mails.tsinghua.edu.cn xgl99@mails.tsinghua.edu.cn>) % at Tsinghua University, Beijing, China. % % For more information, please see % http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm if (nargin<3) error('You must provide the image IM, the window size ws, and C.'); elseif (nargin==3) tm=0; elseif (tm~=0 && tm~=1) error('tm must be 0 or 1.'); end
IM=mat2gray(IM);
if tm==0 mIM=imfilter(IM,fspecial('average',ws),'replicate'); else mIM=medfilt2(IM,[ws ws]); end sIM=mIM-IM-C; bw=im2bw(sIM,0); bw=imcomplement(bw); bw = imresize(bw,[120,120]); imwrite(bw,'bwi.png'); bw = imread('bwi.png');
This is my adaptive thresholding code. Please reply as soon as possible. Thanking you.
