## 3 Results
### Results Based on Real-Time Method  
In order to apply the real-time method, the first step is to select a representative track image. In our experimentation, we use five track images, as shown in Figure 16, that have different pixel dimensions but all have the same center, located at the midpoint of the junction between the red bar support and the contact wire. The experiments were performed on each of the five track images, with average filtering windows of 1 (non-filtering data), 3, 5, 7, 9, and 13 samples. The \"Max Matches\" parameter was 1, and the \"Minimum Score\" parameter was 850, as shown in Figure 11. This value was chosen after conducting various tests on the number of unrecognized cases, as shown in Figure 12c, and the correlation coefficient value, r. It was found that lowering the \"Minimum Score\" parameter leads to a decrease in both the number of unrecognized cases and the correlation coefficient value as the number of incorrect identification cases  
Figure 16: Image tracking dimensions in pixels: (**a**) 16 \(\times\) 32, (**b**) 20 \(\times\) 40, (**c**) 24 \(\times\) 48, (**d**) 28 \(\times\) 56, (**e**) 32 \(\times\) 64. Figure 15: Zigzag length variation at length intervals of 1 m: (**a**) Line 1, (**b**) Line 2.  
increases. Increasing the \"Minimum Score\" setting leads to more unrecognized cases and lower correlation coefficient values. The first experiment refers to the number of unrecognized cases detected when testing the five track images. The tests were determined based on the total number of frames recorded on both Line 1 and Line 2, which corresponds to 6000 points on Line 1 and 6600 points on Line 2. This zone includes the region studied in Section 3.1, between km 505.2 and 510.5. An unrecognized case is identified by a 0 value of the \"Matches\" indicator on the front panel (Figure 11). The results are shown in Table 4.  
It can be observed that when using track image sizes of 20 \(\times\) 40 pixels, the smallest percentage of unrecognized cases was obtained for both Line 1 and Line 2. The second experiment focuses on the correlation coefficient value. The zigzag length values obtained using the first method, referred to as the laboratory method, and shown in Figures 14 and 15, were used as reference values. As previously stated, the zone between km 505.2 and 510.5 has 3900 samples for Line 1 and 4200 for Line 2. Using the second method, measurements were performed on all five-track images and all six average filters for both Line 1 and Line 2. Finally, the correlation coefficient value was calculated for each case between the data obtained with the first and second methods, and the results are shown in Table 5.  
The average window length specifications show that for both Line 1 and Line 2, the optimal average window length is five samples, regardless of the track image dimension used. The highest performance is obtained using a track image dimension of 28 \(\times\) 56 pixels for Line 1 and 20 \(\times\) 40 pixels for Line 2. The explanation for this result is the rail's alignment, which is approximately east-west. Because the measurements were taken between 8 and 10 a.m., the sun's rays influenced them. Figure 17 illustrates the zigzag length variation obtained for Line 1 for each track image dimension. All graphs show plots for the laboratory method, the reference curve, and the \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Line/ Number of Frames**} & \multirow{2}{*}{**Unrecognized Cases/ (\%)**} & \multicolumn{4}{c}{**Track Image (Pixels)**} \\ \cline{3-6}  & & **16 \(\times\) 32** & **20 \(\times\) 40** & **24 \(\times\) 48** & **28 \(\times\) 56** & **32 \(\times\) 64** \\ \hline Line 1/ & Number & 2479 & 2035 & 3810 & 2276 & 2619 \\
6000 & \% & 41.32 & 33.92 & 63.50 & 37.93 & 43.65 \\ \hline Line 2/ & Number & 2701 & 2636 & 4177 & 3278 & 3270 \\
6600 & \% & 40.92 & 39.94 & 63.29 & 49.67 & 49.55 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Relation between the number of unrecognized cases and track image dimension.