Hi...

I am doing a project on the concept of AUTOMATIC NUMBER PLATE RECOGNITION (ANPR) using matlab using artificial neural network for OCR(Optical Character Recognition). here we initially take an image of car number plate or license plate and perform Image enhancement, Image Segmentation and Character Recognition process to display the license plate characters as output of matlab code. I have executed half of the matlab code till dilation process and have got output successfully.. now I have the entire code of the project but I am getting an error and I am unable to remove it.. so can u please suggest ways to remove it or can u please correct that code... or can u please help me in writing a new code regarding this project... or if u have any ideas.. can u please send me the code...

fi = imread('noplate.jpg');

%imshow(fi)

fin = rgb2gray(fi);

imshow(fin);

d=double(fin)

%imshow(fin)

[r c]= size(d)

% Mexican filter operator

filter = [ 0 0 0 -1 -1 -1 0 0 0 ;

0 -1 -1 -3 -3 -3 -1 -1 0;

0 -1 -3 -3 -1 -3 -3 -1 0;

-1 -3 -3 6 13 6 -3 -3 -1;

-1 -3 -1 13 24 13 -1 -3 -1;

-1 -3 -3 -6 13 6 -3 -3 -1;

0 -1 -3 -3 -1 -3 -3 -1 0;

0 -1 -1 -3 -3 -3 -1 -1 0;

0 0 0 -1 -1 -1 0 0 0 ];

% creating image matrix for mexican hat operator

gm = zeros(r,c);

for i=5:2:r-5

for j=5:2:c-5

gm(i,j) = sum(sum(double(fin(i-4:i+4,j-4:j+4)).*filter,2));

end;

end;

% removing the unwanted edges by using a threshold

fh = gm>1200;

%Dilation operation

x = 1;

y =1;

fs = double(fh);

se = ones(3,3);

for x= 3:3:r-20

for y = 3:3:c-20

if(x+50<=r)

xend = x+50;

else

xend = r;

end;

if(y+100<=r)

yend = y + 150;

else

yend = c;

end;

if(sum(fh(x:xend,y))<=35||sum (fh(x,y:yend,2)<=60))

if(sum(fh(x,y:y+3),2)<=3) && (sum(fh(x,y:y+3),2)>2)

fs(x-2:x+2,y-2:y+2)=bwmorph(fh(x-2:x+2,y-2:y+2),'dilate',se);

end;

end;

end;

end;

%imshow(fin)

%image with dilation performed

f=double(fs);

[row col]=size(f);

%initialising a matrix for a segmented image

g=zeros(row,col);

gl=zeros(row,col);

label=1;

n=1;

x=1;

iter=[];

it=0;

ss_prev=0;

nn=[];

sss_mat=[];

for i=1:2:row

for j=1:2:col

r_pt=i;

c_pt=j;

if(g(r_pt,c_pt)==0)

while(true)

|%using 4 neighbour rule|

if(f(r_pt(n),c_pt(n))==1 && g(r_pt(n),c_pt(n))==0)

g(r_pt(n),c_pt(n))=label;

if(r_pt(n)+1<=row)

if(f(r_pt(n)+1,c_pt(n))==1)

r_pt=[r_pt r_pt(n)+1];

c_pt=[c_pt c_pt(n)];

x=x+1;

end;

end;

if(c_pt(n)-1>=1)

if(f(r_pt(n),c_pt(n)-1)==1)

r_pt=[r_pt r_pt(n)];

c_pt=[c_pt c_pt(n)-1];

x=x+1;

end;

end;

if(c_pt(n)+1<=col)

if(f(r_pt(n),c_pt(n)+1)==1)

r_pt=[r_pt r_pt(n)];

c_pt=[c_pt c_pt(n)+1];

x=x+1;

end;

end;

if(r_pt(n)-1>=1)

if(f(r_pt(n)-1,c_pt(n))==1)

r_pt=[r_pt r_pt(n)-1];

c_pt=[c_pt c_pt(n)];

x=x+1;

end;

end;

end;

if(n>=x)

break;

end;

n=n+1;

end;

y1=min(r_pt);

y2=max(r_pt);

x1=min(c_pt);

x2=max(c_pt);

a1=g(min(r_pt):max(r_pt),min(c_pt):max(c_pt));

f1=d(min(r_pt):max(r_pt),min(c_pt):max(c_pt));

[ra ca]=size(a1);

| if(n>=50)|

b1=bwlabel(a1);

ss=regionprops(b1,'euler number');

sss=struct2array(ss);

sss=min(sss);

sss_mat=[sss_mat sss];

if(sss<ss_prev && sss<0 && ca <=190 && ra<=60 && ca>=50 && ra >=15 && mean(mean(f1))<=220)

x_cor1=x1;

y_cor1=y1;

x_cor2=x2;

y_cor2=y2;

ss_prev=sss;

end;

label=label+1;

else

g(r_pt,c_pt)=0;

end;

end;

x=1;

n=1;

it=1;

end;

end;

if(exist('y_cor1')==1)

d(y_cor1:y_cor1+2,x_cor1:x_cor2)=255;

d(y_cor2:y_cor2+2,x_cor1:x_cor2)=255;

d(y_cor1:y_cor2,x_cor1:x_cor1+2)=255;

d(y_cor1:y_cor2,x_cor2:x_cor2+2)=255;

end;

% Segmented licence plate image

d=mat2gray(d);

|lp=d(y_cor1:y_cor2,x_cor1:x_cor2);|

%%% 2. Character Segmentation

%License plate image, characters of wcich are to be segmented

lp1 = d(y_cor1:y_cor2,x_cor1:x_cor2);

[rl cl] = size(lp1);

% Median Filtering

lp = medfilt2(lp1,[3 3]);

% Contrast Enhancement

lpf = imadjust(lp,stretchlim(lp,[0.1 0.5]));

%creating output image matrix

output= zeros(rl,cl);

% Window for local threshold operation

dis = round(cl/7);

% Local threshold operation

for i=1:dis:cl

if(i+dis-1<=cl)

t=threshcal(lpf(:,i:i+dis-1),a);

for i=1:dis:cl

if(i+dis-1<=cl)

t=threshcal(lpf(:,i:i+dis-1),a);

output(:,i:i+dis-1)=lpf(:,i:i+dis-1)<=t;

else

t=threshcal(lpf(:,i:cl),a);

for z1=2:rl-1

for z2=i+5:cl-5

if(mean(mean(lpf(z1-1:z1+1,z2-5:z2+5)))<=t)

output(z1,z2)=1;

end;

end;

end;

output(:,i:cl)=lpf(:,i:cl)<=t;

end;

end;

end;

end;

% Structuring element for erosion operation

se = [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]

output = output - imerode(output,se);

[of lab lpdet] = reggrowl(logical(output),number);

% Segmented characters

lpdet = logical(lpdet);

% Character Recognition

% output String giving licence plate information

lpstr=[];

for i= 1:lab-1

R = lpdet(:,st:st+9);

st = st+10;

b = bwlabel(R);

% Feature extraction

ar = struct2array(regionprops(b,'area'));

or = struct2aarray(regionprops(b,'orientation'))/90;

eu = struct2array(regionprops(b,'eulernumber'))/10;

pe = struct2array(regionprops(b,'perimeter'));

mi = struct2array(regionprops(b,'minoraxislength'));

ma = struct2array(regionprops(b,'majoraxislength'));

temp = logical(R);

% Reflection X and Y coefficient determination

v1 = temp;

v1(:,6:10)=flipdim(temp(:,1:5),2);

vx = (v1 + temp)/2;

vx = vx>=0.5;

xcoef = sum(sum(temp),2)/sum(sum(vx),2);

v2 = temp;

v2(1:12,:) = flipdim(temp(13:24,:),1);

vy = (v2 + temp)/2;

vy = vy >= 0.5;

ycoef = sum(sum(temp),2)/sum(sum(vy),2);

ed = struct2array(regionprops(b,'equivdiameter'))/100;

[val pos] = max(fa);

vcoeff = pe(pos)/ar(pos);

mcoeff = ed(pos);

Rp = [xcoef/ycoef;pe(pos)/ar(pos);mi(pos)/ma(pos)];

answer=find(compet(A2)==1);

if(i<=numel(lpnum))

if(alphamat(answer)==lpnum(i))

numrc = numrc+1;

else

answ = find(alphamat==lpnum(i));

err(answ) = err(answ) + 1;

end;

end;

lpstr = [lpstr alphamat(answer)];

end;

numc = numc + numel(lpnum);

if(strcmp(lpstr,lpnum)==1)

tr = tr + 1;

sr = strcat(num2str(num),'/',num2str(1),'//');

casep = [casep sr];

else

fr = fr +1;

sr = strcat(num2str(num),'/',num2str(1),'/',num2str(answer),'//');

casen = [casen sr];

end;

Olthohoyh

Answer by mahjoub el attar on 4 Apr 2012fi = imread('noplate.jpg');

%imshow(fi)

fin = rgb2gray(fi);

imshow(fin);

d=double(fin)

%imshow(fin)

[r c]= size(d)

% Mexican filter operator

filter = [ 0 0 0 -1 -1 -1 0 0 0 ; 0 -1 -1 -3 -3 -3 -1 -1 0; 0 -1 -3 -3 -1 -3 -3 -1 0; -1 -3 -3 6 13 6 -3 -3 -1; -1 -3 -1 13 24 13 -1 -3 -1; -1 -3 -3 -6 13 6 -3 -3 -1; 0 -1 -3 -3 -1 -3 -3 -1 0; 0 -1 -1 -3 -3 -3 -1 -1 0; 0 0 0 -1 -1 -1 0 0 0 ];

% creating image matrix for mexican hat operator

gm = zeros(r,c);

for i=5:2:r-5

for j=5:2:c-5

gm(i,j) = sum(sum(double(fin(i-4:i+4,j-4:j+4)).*filter,2));

end;

end;

% removing the unwanted edges by using a threshold

fh = gm>1200;

%Dilation operation

x = 1;

y =1;

fs = double(fh);

se = ones(3,3);

for x= 3:3:r-20

for y = 3:3:c-20

if(x+50<=r)

xend = x+50;

else

xend = r;

end;

if(y+100<=r)

yend = y + 150;

else

yend = c;

end;

if(sum(fh(x:xend,y))<=35||sum (fh(x,y:yend,2)<=60))

if(sum(fh(x,y:y+3),2)<=3) && (sum(fh(x,y:y+3),2)>2)

fs(x-2:x+2,y-2:y+2)=bwmorph(fh(x-2:x+2,y-2:y+2),'dilate',se);

end;

end;

end;

end;

%imshow(fin)

%image with dilation performed

f=double(fs);

[row col]=size(f);

%initialising a matrix for a segmented image

g=zeros(row,col);

gl=zeros(row,col);

label=1;

n=1;

x=1;

iter=[];

it=0;

ss_prev=0;

nn=[];

sss_mat=[];

for i=1:2:row

for j=1:2:col

r_pt=i;

c_pt=j;

if(g(r_pt,c_pt)==0)

while(true)

%using 4 neighbour rule

if(f(r_pt(n),c_pt(n))==1 && g(r_pt(n),c_pt(n))==0)

g(r_pt(n),c_pt(n))=label;

if(r_pt(n)+1<=row)

if(f(r_pt(n)+1,c_pt(n))==1)

r_pt=[r_pt r_pt(n)+1];

c_pt=[c_pt c_pt(n)];

x=x+1;

end;

end;

if(c_pt(n)-1>=1)

if(f(r_pt(n),c_pt(n)-1)==1)

r_pt=[r_pt r_pt(n)];

c_pt=[c_pt c_pt(n)-1];

x=x+1;

end;

end;

if(c_pt(n)+1<=col)

if(f(r_pt(n),c_pt(n)+1)==1)

r_pt=[r_pt r_pt(n)];

c_pt=[c_pt c_pt(n)+1];

x=x+1;

end;

end;

if(r_pt(n)-1>=1)

if(f(r_pt(n)-1,c_pt(n))==1)

r_pt=[r_pt r_pt(n)-1];

c_pt=[c_pt c_pt(n)];

x=x+1;

end;

end;

end;

if(n>=x)

break;

end;

n=n+1;

end;

y1=min(r_pt);

y2=max(r_pt);

x1=min(c_pt);

x2=max(c_pt);

a1=g(min(r_pt):max(r_pt),min(c_pt):max(c_pt));

f1=d(min(r_pt):max(r_pt),min(c_pt):max(c_pt));

[ra ca]=size(a1);

| if(n>=50)|

b1=bwlabel(a1);

ss=regionprops(b1,'euler number');

sss=struct2array(ss);

sss=min(sss);

sss_mat=[sss_mat sss];

if(sss<ss_prev && sss<0 && ca <=190 && ra<=60 && ca>=50 && ra >=15 && mean(mean(f1))<=220)

x_cor1=x1;

y_cor1=y1;

x_cor2=x2;

y_cor2=y2;

ss_prev=sss;

end;

label=label+1;

else

g(r_pt,c_pt)=0;

end;

end;

x=1;

n=1;

it=1;

end;

end;

if(exist('y_cor1')==1)

d(y_cor1:y_cor1+2,x_cor1:x_cor2)=255;

d(y_cor2:y_cor2+2,x_cor1:x_cor2)=255;

d(y_cor1:y_cor2,x_cor1:x_cor1+2)=255;

d(y_cor1:y_cor2,x_cor2:x_cor2+2)=255;

end;

% Segmented licence plate image

d=mat2gray(d);

lp=d(y_cor1:y_cor2,x_cor1:x_cor2);

%%% 2. Character Segmentation

%License plate image, characters of wcich are to be segmented

lp1 = d(y_cor1:y_cor2,x_cor1:x_cor2);

[rl cl] = size(lp1);

% Median Filtering

lp = medfilt2(lp1,[3 3]);

% Contrast Enhancement

lpf = imadjust(lp,stretchlim(lp,[0.1 0.5]));

%creating output image matrix

output= zeros(rl,cl);

% Window for local threshold operation

dis = round(cl/7);

% Local threshold operation

for i=1:dis:cl

if(i+dis-1<=cl)

t=threshcal(lpf(:,i:i+dis-1),a);

for i=1:dis:cl

if(i+dis-1<=cl)

t=threshcal(lpf(:,i:i+dis-1),a);

output(:,i:i+dis-1)=lpf(:,i:i+dis-1)<=t;

else

t=threshcal(lpf(:,i:cl),a);

for z1=2:rl-1

for z2=i+5:cl-5

if(mean(mean(lpf(z1-1:z1+1,z2-5:z2+5)))<=t)

output(z1,z2)=1;

end;

end;

end;

output(:,i:cl)=lpf(:,i:cl)<=t;

end;

end;

end;

end;

% Structuring element for erosion operation

se = [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]

output = output - imerode(output,se);

[of lab lpdet] = reggrowl(logical(output),number);

% Segmented characters

lpdet = logical(lpdet);

% Character Recognition

% output String giving licence plate information

lpstr=[];

for i= 1:lab-1

R = lpdet(:,st:st+9);

st = st+10;

b = bwlabel(R);

% Feature extraction

ar = struct2array(regionprops(b,'area'));

or = struct2aarray(regionprops(b,'orientation'))/90;

eu = struct2array(regionprops(b,'eulernumber'))/10;

pe = struct2array(regionprops(b,'perimeter'));

mi = struct2array(regionprops(b,'minoraxislength'));

ma = struct2array(regionprops(b,'majoraxislength'));

temp = logical(R);

% Reflection X and Y coefficient determination

v1 = temp;

v1(:,6:10)=flipdim(temp(:,1:5),2);

vx = (v1 + temp)/2;

vx = vx>=0.5;

xcoef = sum(sum(temp),2)/sum(sum(vx),2);

v2 = temp;

v2(1:12,:) = flipdim(temp(13:24,:),1);

vy = (v2 + temp)/2;

vy = vy >= 0.5;

ycoef = sum(sum(temp),2)/sum(sum(vy),2);

ed = struct2array(regionprops(b,'equivdiameter'))/100;

[val pos] = max(fa);

vcoeff = pe(pos)/ar(pos);

mcoeff = ed(pos);

Rp = [xcoef/ycoef;pe(pos)/ar(pos);mi(pos)/ma(pos)];

answer=find(compet(A2)==1);

if(i<=numel(lpnum))

if(alphamat(answer)==lpnum(i))

numrc = numrc+1;

else

answ = find(alphamat==lpnum(i));

err(answ) = err(answ) + 1;

end;

end;

lpstr = [lpstr alphamat(answer)];

end;

numc = numc + numel(lpnum);

if(strcmp(lpstr,lpnum)==1)

tr = tr + 1;

sr = strcat(num2str(num),'/',num2str(1),'//');

casep = [casep sr];

else

fr = fr +1;

sr = strcat(num2str(num),'/',num2str(1),'/',num2str(answer),'//');

casen = [casen sr];

end;

%% Now your code is a little more clear..