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require a code for automatic licencse plate recognition of vehicles.

Asked by Rakshitha on 29 Mar 2012

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

8 Comments

Image Analyst on 31 Mar 2012

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 on 1 Apr 2012

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

mahjoub el attar on 4 Apr 2012

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.

Rakshitha

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3 Answers

Answer by mahjoub el attar on 4 Apr 2012
Accepted answer
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.

8 Comments

Rakshitha on 6 Apr 2012

K Sir.. but in the line

CC = bwconncomp(LPImageBW); bwconncomp is undefined.

mahjoub el attar on 6 Apr 2012

Hello, "bwconncomp" is an image processing built-in function.
On binary connected component!

Rakshitha on 6 Apr 2012

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'.

mahjoub el attar
Answer by mahjoub el attar on 4 Apr 2012
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....

3 Comments

mahjoub el attar on 4 Apr 2012

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

mahjoub el attar on 4 Apr 2012

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

mahjoub el attar on 4 Apr 2012

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!

mahjoub el attar
Answer by mahjoub el attar on 6 Apr 2012

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.

2 Comments

mahjoub el attar on 8 Apr 2012

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 on 25 Jul 2013

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

mahjoub el attar

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