methode afgerond-ish

content/method.tex

@@ -24,4 +24,6 @@ Verilook is not a stable program, after a random amount of comparisons the Ncore
 \subsection{Get the ROC from every subject}
 Calculation all the ROC\rq{}s will be done with the use of MATLAB. All the comparison scores are stored in a upper triangular matrix. First step is to sort all the comparison scores per subject and per picture. To store this information two structs where generated. The picture struct contains all genuine and imposter scores, the amount of failed matches for the picture is stored as \lq\lq{}noface\rq\rq{} The subject struct contains all genuine and imposter scores as well as all the picture scores of this particular subject, these picture scores contain the same information as the picture struct.
 
-With the use of a loop the true and false match ratings are calculated for each subject. The loop tests for each threshold value between zero and the maximum matching score how many impostor and genuine scores there are. Both the impostor score \[s>t\] and genuine score \[s>t\] is divided by the total amount of impostor and genuine comparisons. The outcome of each threshold is stored in an array which is itself stored in the subject struct. 
+With the use of a loop the true and false match ratings are calculated for each subject. The loop tests for each threshold value between zero and the maximum matching score how many impostor and genuine scores there are. Both the impostor score \[s>t\] and genuine score \[s>t\] is divided by the total amount of impostor and genuine comparisons. The outcome of each threshold is stored in an array which is stored in the subject struct. To generate the overall ROC all these true and false match ratings are summed and divided by the total amount of subjects.
+
+To test the system it is important to visualize all the scores and images. Therefor a MATLAB function is build which will generate \latex script. This document combines per subject all pictures, ROC and scores. The overall scores per subject are represented in a table with the maximum, minimum, mean and standard deviation of the impostor and genuine scores. For further analysis the individual score per picture is added. This enables a human to test what differences in pictures reduce or increase the change on a correct match.