close to these regions. Any change in these regions degrades the
identification performance.
• Overall, with variations in both global and local surgeries, rank-
1 identification accuracies are in the range of 18% (PCA) -
61% (GNN). It is to be noted that these results are computed on
frontal images with neutral expression and proper illumination.
If we include other covariates such as pose, expression and
illumination, the performance may further deteriorate.
• The results of experiment 2 and 3 show that the performance
of face recognition algorithms is slightly better when they are
trained on pre and post surgery images compared to training on
the non-surgery database.
• The correlation analysis of match scores from all six recognition
algorithms is performed using the Pearson correlation coefficient.
It is observed that the algorithms have limited correlation.
The correlation analysis suggests that, for recognizing surgically
altered images, these techniques provide complementary information
and the performance may improve with effective fusion
algorithm.