\section{conclusion}

In general face recognition systems are classified by a single receiver operating characteristic but analyzing a system performance by the single ROCs as in this paper shows a more detailed recognition performance. Although the number of subjects was pretty small to get significant results there were some easy to spot differences between subjects and between different pictures. The failure to capture rate was only a small $1.2\%$. This FCR is made up by 8 pictures who failed almost all face captures and there is a trend in these pictures. All these pictures have a very bad lighting condition, the clothing has far more illumination than the face. But other conditions certainly influence the matching score. Longer hair has a negative influence on the matching scores this has a possible correlation with the gender of the subject. But their are no female subjects with short hair or male subjects with long hair to test this correlation. Unfortunately is this subject group to small to test the Verilook software. But with a larger group of subjects it can be a good procedure to determine where recognition software makes mistakes.