How to plot graph using cell array or store the data into array to prepare it for plotting?

Hello,I store the data into cell array (which is zeta{i,IntDiff_no,Noise_no})and has difficulty to break them into smaller cell array for plotting plotting graph like this.Is there any way to do that or should I change to array such that I store them ? but I don't know how to do it.The code is attached below.Hope to get guidance for solving this problem.Thank you.

%create blank image
w = 200;
h = 200;
blankImage= 255*ones(w,h,3,'uint8');
%position of the letter in the empty cell
position_x = (w+1)/2;
position_y = (h+1)/2;
% varying the font size, start from 10 to 16
font_start = 120;
font_end = 160;
num_fonts = font_start:10:font_end;
% get the number of fonts
numImages = length(num_fonts);
% create a cell array with number of fonts to fill in the image in next step
Output_collection = cell(1, numImages);
Orig_grayImage = cell(1, numImages);
alphabet_segmented = cell(5,5,5);
check_foreground = cell(5,5,5);
alphabet_Uppercase = cell(1,26);
alphabet_Uppercase = ['A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W','X','Y','Z'];
Int_image_array = cell(1, numImages);
A = cell(1, numImages);
Binaryimg{1,i} = cell(1, numImages);
alphabet_orginal = cell(1, numImages);
% alphabet_Image = cell(26,5);
noise_start = 0.01;
noise_end = 0.05;
num_noiseimg = noise_start:0.01:noise_end;
each_noise = length(num_noiseimg);
alphabetNoiseimg_collection = cell(5,5,5);
alphabetSauvImage_collection = cell(5,5,5);
true = 0;
noise_pos = 1;
Int_image = cell(1, numImages);
IntimageFig_pos =1:2:9;
NoiseimgFig_pos =2:2:10;
intensityDifference = 20:20:100;
each_intensityDifference=length(intensityDifference);
zeta = cell(5,5,5);
% for loop to create letter 'A' 
% grayscale
% store into the cell array
% for all_alphabet=1:
for i=1:numImages
    for font_size = num_fonts(i)
        Orgimage= insertText(blankImage,[position_x position_y],'A','Font','Times New Roman','FontSize',font_size,'TextColor','black','BoxColor','w','BoxOpacity',0,'AnchorPoint','Center');
        grayImage= rgb2gray(Orgimage);
        BWImage =  imcomplement(grayImage);
        A{1,i} = BWImage;
        Orig_grayImage{1,i} = A{1,i};
        Binaryimg{1,i} = imbinarize(Orig_grayImage{1,i});
        alphabet_orginal{1,i} = sum(Binaryimg{1,i}(:));
%         figure(i);
%         imshow(A{1,i});
%         impixelinfo;
%         background = BWImage == 0;
%         foreground = ~background;
%         Newforegnd = foreground;
        b=insertText(blankImage,[position_x position_y],'b','Font','Times New Roman', 'FontSize', font_size, 'TextColor','black','BoxColor','w','BoxOpacity',0,'AnchorPoint','Center');
        o=insertText(blankImage,[position_x position_y],'o','Font','Times New Roman Bold', 'FontSize', font_size, 'TextColor','black','BoxColor','w','BoxOpacity',0,'AnchorPoint','Center');
        BWImage_bin = imbinarize(BWImage);
        out = repmat('b',size(BWImage_bin));
        BoldO = '<strong>o</strong>';
        out(BWImage_bin) = 'o';
        display(out);
        Output_collection{1,i} = out;
%         subplot(5,1,i);
%         imshow(BWImage);
%         axis on;
%         title(sprintf('Font size of %d',font_size));
        
        for IntDiff_no=1:each_intensityDifference
            for IntDiff_percentage= intensityDifference(IntDiff_no)
%                 backgroundGrayLevel = IntDiff_percentage;
%                 Int_image = A{1,i};
%                 background_range = A{1,i} ==0; 
%                 Int_image(background_range)= backgroundGrayLevel;
%                 foregroundGrayLevel = backgroundGrayLevel + ((backgroundGrayLevel/100)*255);
%                 foreground_range = A{1,i} ==255;
%                 Int_image(foreground_range) = foregroundGrayLevel;
%                 Int_image_array{i,IntDiff_no} = Int_image;
                highIntensity = (IntDiff_percentage/100)* 255; % 20%
                Int_image = uint8(rescale(A{1,i}, 0, highIntensity));
                Int_image_array{i,IntDiff_no} = Int_image;
                
                figure('Name',sprintf('Font size of %d for Gaussian noise',font_size),'NumberTitle','off');
                for Noise_no =1:each_noise
                    for noise= num_noiseimg(Noise_no)
                        % Apply Gaussiannoise on the alphabet, 
                        %using 0.01 to 0.05 (increament of 0.01 per step)standard deviation
                        NoiseImg = imnoise(Int_image_array{i,IntDiff_no}, 'gaussian',0, noise);
                        alphabetNoiseimg_collection{i,IntDiff_no,Noise_no}=NoiseImg;
                        %apply sauvola's thresholding
                        %m is mean value
                        %k is a constant between 0.2 to 0.5%                       
                        %s is standard deviation 
                        %R is gray level
                        %figure('Name',sprintf('Image of alphabet with font size %d ',font_size),'NumberTitle','off');
                             
                        %S = m* (1 + k * (s/R - 1));
                        %R = 128;
                        %k = 0.2;
                        sauvImage = sauvola(NoiseImg,[150 150]);
                        alphabetSauvImage_collection{i,IntDiff_no,Noise_no} = sauvImage;
                        %for checking total image
                        fprintf('i is%d',i);
                    %   imshow(sauvImage);
                    %   figure('Name','Sauvola thresholding bef and after','NumberTitle','off');
                        Image_segmented = nnz(sauvImage)
                        alphabet_segmented{i,IntDiff_no,Noise_no}= Image_segmented;
                        check_foreground{i,IntDiff_no,Noise_no} = sum(sauvImage(:))
                        zeta{i,IntDiff_no,Noise_no} = alphabet_orginal{1,i}/alphabet_segmented{i,IntDiff_no,Noise_no};
                        if alphabet_segmented{i,IntDiff_no,Noise_no} == check_foreground{i,IntDiff_no,Noise_no}
                            true = true +1;
                        end
                        
                        subplot(5,1,Noise_no);
                        imshow(alphabetNoiseimg_collection{i,IntDiff_no,Noise_no});
                        axis on;
                        title(sprintf('guassian noise std dev is %f and intensity difference %f',noise,IntDiff_percentage));
                    end
                    
                end
           
            end
        end
        figure('Name',sprintf('Font size of %d for Intensity Difference',font_size),'NumberTitle','off');
        for int_no =1:IntDiff_no
            subplot(5,1,int_no);
            imshow(Int_image_array{i,int_no});
            axis on;
            title(sprintf('Intensity difference %d percent for alphabet',intensityDifference(int_no)));
        end
    end
end
fprintf('%d of sauvola image',true);
figure('Name','Image with different font_size','NumberTitle','off');
for font_no =1:numImages
    for each_font = num_fonts(font_no)
        subplot(5,1,font_no); 
        imshow(Orig_grayImage{1,font_no});
        axis on;
        title(sprintf('Image with %d font size',each_font));
    end
end
 figure('Name','Sauvola thresholding','NumberTitle','off');
for font_size = num_fonts(i)
 for IntDiff_no=1:each_intensityDifference
    for IntDiff_percentage= intensityDifference(IntDiff_no)   
         for Noise_no =1:each_noise
            for noise= num_noiseimg(Noise_no)
                subplot(5,1,Noise_no);
                imshow(alphabetSauvImage_collection{i,IntDiff_no,Noise_no});
                title(sprintf('Image with %d font size,%f intensity difference,%d noise',font_size,IntDiff_percentage,noise));
            end
         end
    end
end
end

Answer 1

[Sameer Pujari]

To store cell data in array following command can be used

zeta_array =cell2mat(zeta)

[Tuck Wai Yip]

Hi,I tried cell2mat it is not working on my case,check on my code, you will find out that my cell array is three dimensional. That is the reason why I said I need to find way to break it or even easier way is to change the variable to numerical 2d array to store it when it runs in loop so that it will be convenient for plotting the graph that I need above.

[Tuck Wai Yip]

There is problem for plotting as my x axis that I want to plot ,is in 2d,but the y axis in 3d due to I want to store the value for different parameters in different dimensions.