deletions | additions       diff --git a/chapter_Discussion_label_chap_discussion__.tex b/chapter_Discussion_label_chap_discussion__.tex  index 03b1bed..43a9158 100644  --- a/chapter_Discussion_label_chap_discussion__.tex  +++ b/chapter_Discussion_label_chap_discussion__.tex 
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fact, $\frac{400}{640 \times 480} = 0.13\,\%$. This set the stage for  large speed-ups during live operation. Additionally, it allow for further speed-ups depending on the processing power of the used  CPU.  The evaluation of different maps using the synthetic data showed  considerable differences between the evaluated images. The range of  losses from 0.24 to 0.99 clearly shows the different suitabilities of different maps for the proposed algorithm. In order to visually evaluate the  proposed map evaluation technique, a simple map was constructed with  two repeating tiles. The image with the minimum and the one with the  maximum loss value based on their color histogram are shown in  Figure~\ref{fig:minmaximg}. The different patterns of the images are  clearly visible: while the image with the minimum value fulfills the  desired properties---closeby areas have similar color values, distant  areas are dissimilar, the image with the maximum loss is mainly black  resulting in similar histograms all over the place and leading to  high loss values. This initial evidence can be taken to test the  predictive power of the evaluation algorithm for texton histograms.