# Privacy-Friendly Datasets of Synthetic Fingerprints for Evaluation of Biometric Algorithms
## 3 Research Methodology
### Compilation of Synthetic Datasets  
The high-level overview of the dataset compilation process in shown in Figure 1. We generate our synthetic fingerprints using a combination of model-based and data-driven approaches, which allows for more realistic fingerprints with all necessary characteristics. We first utilize a model-based fingerprint generation tool Anguli as a source of minutiae templates. The fact that Anguli fingerprints do not appear realistic to the human eye plays no role because the only information used is the set of minutiae derived from a pattern. Then, we extract minutiae with the Verifinger SDK [50], convert a minutiae template to a minutiae map using either DL or PM encoding, and finally apply one of the two aforementioned generative models to synthesize realistic fingerprints. The next important step is taking into account the natural distribution of fingerprint patterns among virtual subjects. The intuition behind this is that not all patterns are equally frequent and that some combinations of patterns come together more frequently than other combinations, see, e.g., [[http://fingerprints.handresearch.com/dermatoglyphics/fingerprints-5-fingers-distributions.htm](http://fingerprints.handresearch.com/dermatoglyphics/fingerprints-5-fingers-distributions.htm)]([http://fingerprints.handresearch.com/dermatoglyphics/fingerprints-5-fingers-distributions.htm](http://fingerprints.handresearch.com/dermatoglyphics/fingerprints-5-fingers-distributions.htm)) (accessed on 4 September 2023). It is well known that the most frequent pattern is the ulnar loop (UL), followed by whorl (WH). Arches (AR) and tented arches (TA) are rare patterns that usually appear on all fingers of a subject. Radial loops (RL) are also very rare; they usually appear on index fingers in combination with ulnar loopson all other fingers. We first define 500 virtual subjects with 8 fingers each. Thumbs are disregarded due to a significantly different shape. Table 1 shows the distribution of the most frequent fingerprint patterns over the fingers. Summing up the patterns in this table, we come up with 44 UL, 4 RL, 16 WH, 8 AR, and 8 TA fingerprints for 10 subjects. Exactly the same distribution of basic patterns is scaled up to 50 subjects, resulting in 4000 fingerprints. The distribution of basic patterns in our synthetic datasets is visualized in Table 2). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Num. of** & \multicolumn{4}{c}{**Left Hand**} & \multicolumn{4}{c}{**Right Hand**} \\ \cline{2-10}
**Subjects** & **Index** & **Middle** & **Ring** & **Pinky** & **Index** & **Middle** & **Ring** & **Pinky** \\ \hline
50 & RL & UL & UL & UL & RL & UL & UL & UL \\ \hline
50 & UL & UL & WH & UL & UL & UL & WH & UL \\ \hline
50 & AR & UL & UL & UL & AR & UL & UL \\ \hline
50 & WH & WH & UL & UL & WH & WH & UL \\ \hline
50 & AR & AR & UL & UL & AR & AR & UL & UL \\ \hline
50 & AR & TA & TA & TA & AR & TA & TA & TA \\ \hline
50 & RL & TA & UL & UL & RL & TA & UL & UL \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Common distributions of basic fingerprint patterns over fingers. UL—ulnar loop, RL—radial loop, WH—whorl, AR—arch, and TA—tented arch. An ulnar loop on a right hand is represented by a left loop fingerprint image just as an ulnar loop on a left hand is represented by a right loop image. This means that considering the equal proportion of ulnar/radial loops on the right and left hands, we need to generate the same number of right and left loop images. In particular, we need 2400 loops in total, split into 1200 right and 1200 left loops. For the purpose of basic pattern generation, we apply Anguli to generate 1200 right loops, 1200 left loops, 800 whorls, 400 arches, and 400 tented arches. According to Table 1, the fingerprints are distributed between 500 subjects and their eight fingers: right hand index, middle, ring, and pinky fingers; and left hand index, middle, ring, and pinky fingers.