require a code for automatic licencse plate recognition of vehicles.

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;

Thanking you, With regards, Rakshitha

[Walter Roberson]

http://www.mathworks.com/matlabcentral/answers/13205-tutorial-how-to-format-your-question-with-markup

[Walter Roberson]

It makes it easier for us if you tell us what error you see, on which line. We do not have your images, so we cannot run the program to see the results ourselves.

[Image Analyst]

You say "I am getting an error and I am unable to remove it" - well apparently you did remove it from your question. We have no idea what the error is because you didn't include it.

[Rakshitha]

Sir I am getting the error as

"??? Undefined function or variable 'y_cor1'.

Error in ==> prog_part1 at 152

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

May be the actual problem may lie in the Neighbour rule loop.. because variable 'x' is not getting incremented (donno why 'x' is not satisfying any condition) and hence may satisfy 108th line

if(n>=x)

break;

and ends in break.. so the next 'if' loop of line 120 may not satisfy and the further inner loops line 126

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

may not be working... may be it not entering the main 'if' loop of line 120 itself and hence that loop may not be working... I am not sure whether this is the reason or not.. plese help me in getting the output through this code as early as possible because i have vry less time for implementation.

[Rakshitha]

Input image can be any image of a number plate or licencse plate of a car.

[Image Analyst]

Can you learn how to use the debugger to set breakpoints and step through your code to find out why loops are not getting entered, variables aren't getting assigned and are undefined/empty? That is FAR more efficient than asking us to do that for you. You will discover problems with your code faster that way than posting here and waiting for us. This looks like an easy, straightforward debugging task to me.

[Rakshitha]

K Sir, thank you so much... i will try using debuggers.

[mahjoub el attar]

Hello Rakshita.

With respect....

I'd like to solve your problem.

But code is not clear, not segmented and not commented.

It's big time consuming answer.

If you expect help, you need to provide clear and readable code.

Friendly.

[aziz rehman]

Hello sir .. Sir can you provide the image on which you run this code? The images that you tested for this code.

[Hammad Sarwar]

Hello Sir can u help in color detection using matlab

[Walter Roberson]

Hammad Sarwar: the person who posted this question has not been active for nearly 4 years, and will not be notified of your comment. You would be more likely to get a response if you started a new Question and described what you need to do.

http://www.mathworks.com/matlabcentral/answers/6200-tutorial-how-to-ask-a-question-on-answers-and-get-a-fast-answer

[Image Analyst]

Hammad, see my File Exchange for several color segmentation demos http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862. In addition, try the Color Thresholder app on the Apps tab of the tool ribbon of MATLAB.

Answer 1

[mahjoub el attar]

function  [LPImageGray,LPImageBW,BW2,BW3,stats,LPImageTH,EdgeImage,imrefdata,ids,im] = AnprEngine( LPImage,thresh)
%ANPRENGINE Summary of this function goes here
%   Process image input analytics and output licence plate alphanumeric string
%   Based on static image
tic

Variables Initialization EligibleBands = zeros(3,2); Pointer = 1; Sensing = 0; MinimalHeight = 15;

srcData = load('AnprSysData.mat');
imrefdata = srcData.AlphaNumRef;
im = [];
C = zeros(109);
% toc

Pre-process LPImage

LPImageGray = rgb2gray(LPImage);
LPImageTH = imtophat(LPImageGray,strel('ball',12,7));%Close ball 18 7/ Far ball 12 4 
imadjust(LPImageTH,[0;0.1],[0;1]);
%[EdgeImage, thr, gv, gh] = edge(LPImageGray,'sobel','nothinning');
[EdgeImage, ~, ~] = edge(LPImageGray,'sobel');
LPImageBW = ~im2bw(LPImageTH,thresh);
%LPImageVH = edge(LPImageGray, 'sobel',0.11,'vertical');
%sz = size(LPImage);
toc

Skew detection Spacial Transformation correction

Process Image ROI candidates, Heuristic and Bands Elimamination

toc
ProjectionVH = sum(LPImageVH,2);%Compute sum of Horizontal Projection of vertical lines
maxIndexValue = find(ProjectionVH == max(ProjectionVH), 1,'last');%Find Max Index Value of ProjectionVH 1*m Matrix
% Locate most significative eligible bands.
sensor = mean(ProjectionVH);% Define standard deviation of ProjectionVH to find eligible bands 
for idx = 1:sz(1,1)
    if(ProjectionVH(idx) > sensor && Sensing == 0)
        Sensing = 1;
        EligibleBands(Pointer, 1) = idx;
    end
    if(ProjectionVH(idx) < sensor && Sensing == 1)
        Sensing = 0;
        EligibleBands(Pointer, 2) = idx;
        if((EligibleBands(Pointer, 2)-EligibleBands(Pointer, 1))>MinimalHeight)
        Pointer = Pointer + 1;
        end
    end
end
for i = 1:sz(1,1)
    if(i < EligibleBands(1,1) || i > EligibleBands(1,2))
        LPImageBW(i,:) = 0;
    end
end

Locate Licence Plate Bands

Blobs Analysis

CC = bwconncomp(LPImageBW);
stats = regionprops(CC, 'Area','BoundingBox','Image');
ids = find([stats.Area] > 8 & [stats.Area] < 250);
BW2 = ismember(labelmatrix(CC),ids);
toc

Blobs Analysis

CC2 = bwconncomp(~LPImageBW);
stats2 = regionprops(CC2,'Area','BoundingBox','Eccentricity');
ids2 = find([stats2.Area] > 20 & [stats2.Eccentricity] > 0.95);
BW3 = ismember(labelmatrix(CC2),ids2);
%BW3 = [];% ismember(labelmatrix(CC2),ids2);
toc

Pre-OCR

for k=1:length(ids)
    imOriginal =  stats(ids(k)).Image;
    BB = stats(ids(k)).BoundingBox;
    NormIm{1,1} =  resizem(imOriginal,[60,30]);
    NormIm{2,1} =  BB(4)/BB(3);
    [NormIm{3,1} NormIm{4,1}, NormIm{5,1}] = getMaxCorrelationRate(NormIm{1,1},imrefdata);
    if(BB(4)/BB(3)>=1.4 && BB(4)/BB(3)<=2 || BB(4)/BB(3)>=3 && BB(4)/BB(3)<=10)
        im = [im NormIm];

      %imshow(cell2mat(PD(1,:))) %to display all column in first row on NormIm
      %output
      %imshow(cell2mat(E2(2)))
      end
  end
  toc

OCR Function

      function [Rate,id, Letter] = getMaxCorrelationRate(imOriginal,imrefdata)
              for n=1:length(imrefdata)
                  Rates(n) = corr2(imOriginal,cell2mat(imrefdata(1,n)));
              end
              [Rate,id] = max(Rates);
              if(Rate>0.48)
                  Letter = imrefdata{2,id};
              else
                  Letter ='';
              end;
      end

OCR AlphaNumerical resolution

LPNumber = 'Hello Plate';

%%Output
end
% It uses correlation instead of ANN. 
% All is in AnprSysData.mat file Chars are indexed from 1 to 109

% Author Mahjoub El attar 2002-2006 for smartKam. For more information feel free to contact me at my profile email contact address.

[mahjoub el attar]

This is a generic and working function for study purpose.

Several critical steps are solved here.

(License plate detection, features extraction, etc...)

But many parts that make the code very robust were deleted, cause I use it in my business.

[Rakshitha]

Thank u so much Sir. I will try executing this code.

[Rakshitha]

Sir, in the below statement what better values of threhold and gv should be given.

%[EdgeImage, thr, gv, gh] = edge(LPImageGray,'sobel','nothinning');

[EdgeImage, ~ ,~ ] = edge(LPImageGray,'sobel');

or can it be left blank ... if so it shows error as

??? Error: File: AnprEngine.m Line: 23 Column: 14

Expression or statement is incorrect--possibly unbalanced (, {, or [.

??? Error: File: AnprEngine.m Line: 23 Column: 20

Unbalanced or unexpected parenthesis or bracket.

[Rakshitha]

where is this AnprSysData.mat file available ?

[mahjoub el attar]

Threshold should be between 0.12 to 0.21. My default one is 0.17

The AnprSysData.mat is located here: http://smartkam.com/matlabFiles/AnprSysData.mat

[Rakshitha]

K Sir.. but in the line

CC = bwconncomp(LPImageBW); bwconncomp is undefined.

[mahjoub el attar]

Hello, "bwconncomp" is an image processing built-in function.

On binary connected component!

[Rakshitha]

Sir, for

LPImageBW = ~im2bw(LPImageTH,thresh);

as you have said I gave the thresh value= 0.17 ie

LPImageBW = ~im2bw(LPImageTH,0.17);

later for CC = bwconncomp(LPImageBW); it shows error as

??? Undefined function or method 'bwconncomp' for input arguments of type 'logical'.

Answer 2

[Ahmad Madzarul Musa]

Undefined function or variable 'y_cor1'.

Error in trynerror (line 278) lp=d(y_cor1:y_cor2,x_cor1:x_cor2);

[Walter Roberson]

Which version of the code are you using?

Answer 3

[mahjoub el attar]

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

[mahjoub el attar]

Let's see what Mexican License Plate looks like...

[mahjoub el attar]

http://www.olavsplates.com/foto/mex_xyx4448.jpg

[mahjoub el attar]

Some parts look good, but some are not.

Don't forget the basics of algo programming.

If you cannot tell it well, you cannot program it as well.

You don't need mexican filter.

Any license plate in the world is based on contrast.

It should look like this one under!

[Mutturaj Hubballi]

this code showing an error in the lp line..what is that lp variable its not taking into it

[Twinkle Pajiyar]

its giving an error on line lp=d(y_cor1:y_cor2,x_cor1:x_cor2); as Undefined function or variable 'y_cor1'.

Answer 4

[mahjoub el attar]

Hi, You must use it as this. A = AnprEngine(Image, 0.17); Ok.... let me zip all files with the User-Interface "GUI" and testing snapshots.

[mahjoub el attar]

Hello.

I'm on an urgent and time consuming work that makes me working all the week-end.

Yes I'm sorry I didn't sent you all files yet.

Hope I'll get some time to zip all this by tomorrow.

Friendly

[Ismail Saheb Bagalkote]

air can i get a final GUI because same i want to for paper currency thankig you

[[e-mail] sidharth]

sir i want car number plate auto crop code

[Walter Roberson]

[e-mail] sidharth : license plates vary a lot from country to country and sometimes even within any one country. The EU more or less standardizes the plates, but other countries do not. Do not assume that plates will be rectangular. Do not assume that license plates will contrast with the color of the car. Do not assume that license plates will use the so-called "Arabic numerals" that are used in English. In the past I have posted examples of plates that violate the common assumptions about what number plates look like.

Because of these points, it is fairly difficult to create a program that automatically crops all license plates.

[sivakumar s]

please send me the source code and examples

email -- [e-mail]

[Shaik Vaseem]

Can you please suggest us a solution that how the frames are called into the code automatically to detect the number plate from that frames.

[Walter Roberson]

No, we cannot suggest any solution to that. License plates can look like anything . If you were to look at a car and not see any obvious plate, but happened to notice that the car had one pink tailpipe and one green tailpipe, then the exact color and positions of the tailpipes could be the license plate. The "baby on board" sticker on the side of the car could be the license plate.

In order for a solution to be practical, you would need to restrict your scope to only specific kinds of license plates. And even then note what I wrote above about "Do not assume that license plates will contrast with the color of the car."