# Personal Identification Using Embedded Raspberry Pi-Based Face Recognition Systems
## 3 Verification System
### Selecting the Similarity Threshold
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Set Similarity** & **User No. 1** & **User No. 2** & **User No. 3** & **User No. 4** & **User No. 5** & **User No. 6** \\
**Threshold** & **([PERSON])** & **([PERSON])** & **([PERSON])** & **([PERSON])** & **([PERSON])** & **([PERSON])** \\ \hline
0 & [PERSON] & Kacper & Kacper & Kacper & Kacper & Kacper \\
10 & [PERSON] & Kacper & Kacper & Kacper & Kacper & Kacper \\
20 & [PERSON] & Kacper & Kacper & Kacper & Kacper & Kacper \\
30 & [PERSON] & Kacper & Kacper & Kacper & Kacper & [PERSON] \\
40 & [PERSON] & [PERSON] & [PERSON] & [PERSON] & [PERSON] & [PERSON] \\
50 & [PERSON] & [PERSON] & [PERSON] & [PERSON] & [PERSON] & [PERSON] \\
60 & [PERSON] & unknown & [PERSON] & [PERSON] & [PERSON] & unknown \\
70 & [PERSON] & unknown & [PERSON] & [PERSON] & unknown & unknown \\
75 & [PERSON] & unknown & unknown & [PERSON] & unknown & unknown \\
80 & [PERSON] & unknown & unknown & [PERSON] & unknown & unknown \\
85 & [PERSON] & unknown & niezmana & [PERSON] & unknown & unknown \\
90 & [PERSON] & unknown & niezmana & unknown & unknown & unknown \\
95 & unknown & unknown & niezmana & unknown & unknown & unknown \\
100 & unknown & unknown & unknown & unknown & unknown & unknown \\ \hline \end{tabular}
\end{table} 
Table 1: The results of facial recognition with only User No. 1 ([PERSON]) introduced into the system and varying similarity thresholds. Figure 11: Test group users (photos from the application database): (**a**) User No. 1 ([PERSON]); (**b**) User No. 2 ([PERSON]); (**c**) User No. 3 ([PERSON]); (**d**) User No. 4 ([PERSON]); (**e**) User No. 5 ([PERSON]); (**f**) User No. 6 ([PERSON]). The biometric similarity between User No. 1 and other users was analyzed. User No. 4 was identified as the most similar, with approximately 80% biometric similarity to User No. 1. In contrast, Users No. 2 and No. 6 were the least similar, showing about 50% similarity. When the similarity threshold was set above 90%, the system experienced difficulties recognizing the previously registered user. These challenges arose from limitations in camera resolution, system performance, variations in external conditions (e.g., identical facial expressions or positions in both images. Such factors result in variations in certain anthropometric distances, causing discrepancies between the tested image and the reference data matrix. From the initial test, it was concluded that a similarity threshold of 85-90% offers the most balanced performance. However, determining the optimal threshold cannot rely solely on identification accuracy. The recognition time is equally critical, as users should not spend excessive time adjusting their position or facial expression for a successful match. In addition to being accurate and reliable, the system must be efficient and user-friendly. Upon detecting a face in the image, the application identifies the individual by name if they are in the database or labels them as \"unknown\" if no match is found. To ensure usability, it was necessary to define a recognition time threshold. Identification attempts lasting more than 2 min, even with adjustments to position or expression, were considered failures. The recognition times recorded during the first test are summarized in Table 2.  
Identification process times (Table 2) confirm that the most appropriate threshold value is in the 80-90% similarity range. Due to anthropometric distance similarities, individuals with biometric features similar to the first user (User No. 4) experience longer face recognition times despite positive recognition results at an 85% similarity threshold. We can also observe that increasing the similarity threshold causes the times to increase non-linearly, similar to exponential growth (Figure 12). Users No. 1, 4, and 6 were entered into the database for the next test. The threshold value was varied with each identification attempt, and if the recognition time exceeded two minutes, the attempt was deemed negative.