# I work on the project fake currency detection by MATLAB but I get a error i try to solve but i dont find solution

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rohit il 28 Feb 2023
Risposto: rohit il 6 Apr 2023
#THIS IS THE CODE i mark the line down the code
[FILENAME,PATHNAME]=uigetfile( '*.jpg', 'Select the Image');
FilePath=strcat(PATHNAME,FILENAME);
disp('The Image File Location is');
disp(FilePath);
figure, imshow(DataArray,map);
title('Input Image');
%Seperate Channel
r_channel=DataArray(:,:,1);
b_channel=DataArray(:,:,2);
g_channel=DataArray(:,:,3);
%Noise Removal
r_channel=medfilt2(r_channel);
g_channel=medfilt2(g_channel);
b_channel=medfilt2(b_channel);
%restore channels
rgbim(:,:,1)=r_channel;
rgbim(:, :,2)=g_channel;
rgbim(:,:,3)=b_channel;
figure,imshow(uint8(rgbim));
title('Denoised Image');
%RGB to Gray
Igray= 0.30*r_channel + 0.59*g_channel + 0.11*b_channel;
figure,imshow(uint8(Igray));
title('Gray Image');
%Edge Detection
y=double(Igray);
fl=zeros(3,3,5);
fl(:,:,1) = [1 2 1;0 0 0;-1 -2 -1]; %vertical
fl(:,:,2) = [-1 0 1;-2 0 2;-1 0 1]; %horizontal
fl(:,:,3) = [2 2 -1;2 -1 -1; -1 -1 -1]; %45 diagonal
f1(:,:,4) = [-1 2 2; -1 -1 2; -1 -1 -1];%135 diagonal
fl(:,:,5) = [-1 0 1;0 0 0; 1 0 -1]; %non directional
for i= 1:5
g.im(:,:,i) = filter2(fl(:,:,i),y);
end
title('Edge Detection');
Avg=mean2(Igray);
if(Avg>202 && Avg<207)
elseif(Avg>175 && Avg<180)
elseif(Avg>190 && Avg<195)
elseif(Avg>209 && Avg<214)
end
figure,imshow(uint8(DataArray));
title('ROI-Extract Texture & Statistical Features');
hold on
for n=1 :size(A,1)# i GET THE ERROR IN THIS LINE A IS 'ROI-Extract Texture & Statistical Features
rectangle('Position',A(n, :), ' EdgeColor', 'r', 'LineWidth',4)
end
pause(1)
figure, imshow(edhist);
title('ROI-Extract Edge & Shape Features');
hold on
for n=1:size(A,1)#---------------------------------------------------------------------------------------------------------------------------------------
rectangle('Position',A(n,:), 'EdgeColor', 'r','LineWidth',4)
end
pause(1)
SFL_Data=zeros(size(A,1),6);
SSL_Data=zeros(size(A,1),12);
for n=1 :size(A,1)
imcropgray imcrop(Igray, A(n, :));
Img_data=imcropgray;
%STATISTICAL FEATURES
%First Level Feature
Mean mean2(Img_data);
Variance = mean2(var(double(Img_data)));
Kurtosis=kurtosis(double(Img_data(:)));
stats = graycoprops(Img_data, 'Contrast Correlation Energy Homogeneity');
Energy=stats.Energy;
Contrast = stats.Contrast;
Entropy=entropy(Img_data);
FL_Feat=[Mean Variance Kurtosis Energy Contrast Entropy];
FL_Feat(isnan(FL_Feat))=0;
%disp('First Level Feature');
%disp(FL_Feat)
SFL_Data(n,:)=FL_Feat;
%Second Level Feature
offsets=[0 1; -1 1; -1 0; -1 -1]; %0 °, 45 °, 90 °, 135 °
GLCM1=graycomatrix(Img_data, 'NumLevels' ,8, 'Offset',offsets);
GLCM2 = graycomatrix(Img_data, 'NumLevels',32, 'Offset',offsets);
stats=graycoprops(GLCM1, 'Contrast Correlation Energy Homogeneity');
statsl= graycoprops(GLCM2, 'Contrast Correlation Energy Homogeneity');
Correlation=[mean(stats.Correlation) mean(statsl.Correlation) ];
ASM=[mean(stats.Energy) mean(statal.Energy)];
Homogeneity=[mean(stats.Homogeneity) mean(statsl.Homogeneity) ];
IDM=[Inverse Diff(GLCM1) Inverse Diff(GLCM2)];
Max_prob=[Maximium_Prob(GLCM1) Maximium_Prob(GLCM2)];
Entropy=[entropy(GLCM1) entropy(GLCM2)];
SL_Feat=[ASM Correlation Homogeneity IDM Max_prob Entropy];
SL_Feat(isnan(SL_Feat))=0;
%disp('Second Level Feature')
%disp(SL_Feat)
SSL_Data(n,:)=SL_Feat;
end
ST_feat=[mean(SFL_Data) mean(SSL_Data)];
disp('Statistical Features')
disp(ST_feat);
EF_Data=zeros (size(A,1),7);
for n=1:size(A,1)
imcropedge = imcrop(edhist,A(n, :));
%Edge Features
results=regionprops(imcropedge,'Area' , 'EulerNumber', 'Orientation' , 'BoundingBox' ,'Extent',...
'Perimeter', 'Centroid','Extrema' , 'PixelIdxList', 'ConvexArea', ...
'FilledArea', 'PixelList','ConvexHull', 'FilledImage', ' Solidity',...
'Convex Image', 'Image', 'SubarrayIdx' ,'Eccentricity','MajorAxisLength',...
'EquivDiameter', 'MinorAxisLength', 'EulerNumber');
NR=vertcat(results. BoundingBox);
Circularity=zeros(size(NR,1));
Eccentricity=zeros(size(NR,1));
Convexity=zeros(size(NR, 1));
Area=zeros(size(NR,1));
Compactness=zeros(size(NR,1));
Extent=zeros(size(NR,1));
Solidit=zeros(size(NR,1));
for ii=1:size(NR,1)
Circularity(ii) = ((results(ii) .Perimeter) .^2 )./ (4* (pi* (results(ii).Area)));
Circularity(isnan(Circularity))=0;
Circularity(isinf(Circularity)) = 0;
Compactness(ii)=(4* results(ii) .Area*pi)/(results(ii) .Perimeter).^2;
Compactness(isnan(Compactness))=0;
Compactness(isinf(Compactness)) = 0;
Convexity(ii)=results(ii).ConvexArea;
Convexity(isnan(Convexity))=0;
Convexity(isinf(Convexity)) = 0;
Area(ii)=results(ii) .Area;
Area(isnan(Area))=0;
Area(isinf(Area)) = 0;
Eccentricity(ii)=results(ii) .Eccentricity;
Eccentricity(isnan(Eccentricity) )=0;
Eccentricity(isinf(Eccentricity)) = 0;
Extent(ii)=results(ii) .Extent;
Extent(isnan(Extent) )=0;
Extent(isinf(Extent) ) =0;
Solidity(ii)=results(ii).Solidity;
Solidity(isnan(Solidity))=0;
Solidity(isinf(Solidity)) = 0;
end
SF=[mean2(Area) mean2 (Solidity) mean2 (Convexity) mean2 (Circularity) mean2 (Eccentricity) mean2(compactness) mean2(Extent)];
EF_Data(n, :)=SF;
end
EDF_feat=mean(EF_Data);
disp('Edge Features' )
Tfeat=[ST_feat EDF_feat];
xdata = [Train_dataP;Train_dataN];
group=[Train_LabP;Train_LabN];
svmTrain = fitcsvm(xdata,group, 'kernel_function','rbf');
ClassfyResult = ClassificationSVM(svmTrain,Ifeat);
if(Classfy_Result == 1)
figure,imshow(DataArray,map);
title('Currency Type: Real');
msgbox('Currency Type: Real');
else
figure, imshow(DataArray,map);
title('Currency Type: Fake');
msgbox('Currency Type: Fake' );
end
pause(2)
##### 6 CommentiMostra 5 commenti meno recentiNascondi 5 commenti meno recenti
Image Analyst il 1 Mar 2023
Modificato: Image Analyst il 1 Mar 2023
He did not say "remove the edge colour", he said to remove the space in front of EdgeColor. So it's 'EdgeColor', NOT '<space>EdgeColor'.

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### Risposta accettata

Jan il 28 Feb 2023
Spostato: Jan il 28 Feb 2023
As I've written already, the problem is here:
rectangle('Position',A(n, :), ' EdgeColor', 'r', 'LineWidth',4)
% ^ no space in front
##### 4 CommentiMostra 3 commenti meno recentiNascondi 3 commenti meno recenti
Jan il 1 Mar 2023
@Image Analyst: Thanks. You've saved my day. 🍪

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### Più risposte (2)

Image Analyst il 28 Feb 2023
##### 15 CommentiMostra 14 commenti meno recentiNascondi 14 commenti meno recenti
AFA il 6 Apr 2023
yes.

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rohit il 6 Apr 2023
thanks to everyone to helping me specialy @Image Analyst@Jan
##### 0 CommentiMostra -1 commenti meno recentiNascondi -1 commenti meno recenti

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