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

#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);
[DataArray,map]=imresize(imread(FilePath),[300,650]);
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)
    load 100.mat
elseif(Avg>175 && Avg<180)
    load 200.mat
elseif(Avg>190 && Avg<195)
    load 500.mat
elseif(Avg>209 && Avg<214)
    load 2000.mat
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];
load Pdata.mat
load Ndata.mat
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)

[Rik]

You made variables magically appear in your workspace by using load like you did. Now you are facing the problem that you have no idea where A came from, nor what other variables may have been created.

Have a read here and here. It will greatly improve your chances of getting an answer. Try to make a MWE so we can run your code without any other dependencies and can reproduce your issue. The best way to do this is to use the code section in the editor and use the run button. That way you can make sure we will see the same error message as you do.

[rohit]

can you help me sir

[Jan]

@rohit: Plese post a copy of the complete error message.

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

It is unlikely, that this for command causes an error. As soon as you post the message, the readers do not have to guess, what the problem is.

In the following line you try to set the property ' EdgeColor'. This does not exist due to the leading space. Remove it.

[rohit]

Error using rectangle

There is no EdgeColor property on the Rectangle class.

Error in code3 (line 55)

rectangle('Position',A(n, :), ' EdgeColor', 'r', 'LineWidth',4)

[rohit]

@Jan when i remove the edge colour this message was appear

Error using rectangle

There is no EdgeColor property on the Rectangle class.

Error in code3 (line 55)

rectangle('Position',A(n, :), ' EdgeColor', 'r', 'LineWidth',4)

[Image Analyst]

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'.

Answer 1

[Jan]

As I've written already, the problem is here:

rectangle('Position',A(n, :), ' EdgeColor', 'r', 'LineWidth',4)
%                              ^ no space in front

[rohit]

@Jani overcome this can you help me ??

[Image Analyst]

I thought he did. Did you try removing the space and trying it?

rectangle('Position', A(n, :), 'EdgeColor', 'r', 'LineWidth', 4)

If not, then why not? If you did, did that solve it?

[rohit]

no your @Image Analyst solution help me out

[Jan]

@Image Analyst: Thanks. You've saved my day. 🍪

Answer 2

[Image Analyst]

I answered in your comment to the person who wrote this code and did not define the A

https://www.mathworks.com/matlabcentral/answers/1845863-i-want-to-define-a-for-roi-i-don-t-know-to-to-define-where-to-define#comment_2637880

[rohit]

@Image Analyst undefined function or variable 'Inverse_Diff'. how can i solve this

[Image Analyst]

I have no idea. I do not see 'Inverse_Diff' in any code in this question.

[rohit]

 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;

[rohit]

second level feature IDM=IDM=[Inverse Diff(GLCM1) Inverse Diff(GLCM2)];

[Image Analyst]

There you have "Inverse Diff(GLCM1)" which is different than "Inverse_Diff(GLCM1)". Which is it supposed to be?

[rohit]

"Inverse_Diff(GLCM1)" i write this in code and then i also get the error than is undefine function or variable !!!

[Image Analyst]

Inverse_Diff() is not a built-in function. Please attach your Inverse_Diff.m file with the paperclip icon.

[rohit]

there is no file regarding this

[Image Analyst]

Then you can't use that function since no function by that name exists.

[rohit]

but it is essential to use this function then what i do

[Jan]

@rohit: You do not have a function called Inverse_Diff, but you have to use this function? Then you have to write it.

[AFA]

@rohit you find answer of this error. Plz help me.

IDM=[Inverse Diff(GLCM1) Inverse Diff(GLCM2)];

[rohit]

hi @AFA i done my project

do you need help so you can contact me on my mail id [e-mail]

[rohit]

@AFA you also work on fake currency detector

[AFA]

yes.

Answer 3

[rohit]

thanks to everyone to helping me specialy @Image Analyst@Jan