MATLAB: Calculation of TP, FP,TN and FN for the dataset

https://in.mathworks.com/matlabcentral/fileexchange/34412-fast-and-efficient-spectral-clustering

Iam working on a dataset of 150 images for pothole detection. The ouput is a binary image after applying the morphological operations and i want to calculate the number of TP, FP,TN and FN for the dataset.
For example in the output image, the pothole area is covering the black pixels and the background is of white pixels for all set of images. The below image is the original image and the corresponding binary image is the output.
The below is the code for the dataset iam working…….how to calculate the parameters TP,FP,TN,FN for the below code.. 
clc;
clear all;
close all;
myTrainingFolder = 'C:\Users\Admin\Desktop\New folder (2)';
trainingSet = imageDatastore(myTrainingFolder,'IncludeSubfolders', true,  'LabelSource', 'foldernames');
imageSize = [300 300];
spectra = imageSize;
trainingSetLabels = countEachLabel(trainingSet);
numImagesTraining = numel(trainingSet.Files);
for j = 1 : numImagesTraining
    I = imread(trainingSet.Files{j});
    img = imresize(I,imageSize);     
   spectra = spectralclust(img);% spectral clustering
 BW = imbinarize(spectra,1);
imagen = bwareaopen(BW,1); 
se=ones(3,3);
img1 = imerode(imagen,se);  %final output after applying erosion
    numWhitePixels = sum(img1(:));
    numBlackPixels = sum(~img1(:));
   percentageWhite = nnz(img1) / numel(img1);
   percentageBlack = nnz(~img1) / numel(img1);
   if (  percentageBlack <= percentageWhite)
    disp('it is a pothole');
    imwrite(img1,[['C:\Users\Admin\Desktop\Major Project\training_output\outputp_' num2str(j)] '.png']);
else
    disp('it is not a pothole'); 
   imwrite(img1,[['C:\Users\Admin\Desktop\Major Project\training_output\outputnp_' num2str(j)] '.png']);
   end
end
thank you in advance

Best Answer

For basic understanding, lets say seg_im is the segmented binary image as per ROI and gold_im is the gold data/ground truth image data (Pixel by Pixel), considering white pixels ROI, black pixels non ROI 
TP=sum(~xor(seg_im,gold_im));
TN=sum(~seg_im && ~gold_im)); %Sum all black pixels in seg_im=gold_im
Apply the simmilar logical operators for FP and FN
FP=ROI not there but detected as ROI 
FN=ROI there but not detected as ROI
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