# A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images
## 3 Experiments and Results
### Evaluation
#### 3.2.2 Quantitative Evaluation
The range of lengths of ships is from 40 m to 400 m, and even some ships whose lengths are below 50 m (less than the image spatial resolution of the GF-4 satellite) can be identified after ship detection and tracking. From another perspective, it also reflects the strong capabilities of the GF-4 satellite for marine surveillance. 79 ships verified by AIS data in two ROIs are used to assess the motion state. Figure 6 shows the comparisons of motion state estimation between the tracking results and AIS data in five frames. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**ROI**} & \multicolumn{3}{c}{**Before Tracking**} & \multicolumn{3}{c}{**After Tracking (Only Position)**} & \multicolumn{3}{c}{**After Tracking (Position + Amplitude)**} \\ \cline{2-9}  & **Precision** & **Recall** & **F-Score** & **Precision** & **Recall** & **F-Score** & **Precision** & **Recall** & **F-Score** \\ \hline
1 & 26.6\% & 79.6\% & 39.9\% & 93.0\% & 75.5\% & 83.3\% & 97.6\% & 77.3\% & 86.3\% \\
2 & 74.5\% & 94.1\% & 83.2\% & 97.8\% & 91.8\% & 94.7\% & 99.0\% & 92.9\% & 95.9\% \\ Total & 47.6\% & 89.0\% & 62.0\% & 96.3\% & 86.1\% & 90.9\% & 98.5\% & 87.4\% & 92.6\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Ship detection and tracking performance of the experiment. Figure 4: Detection and tracking results in two ROIs. (**a,b**) Intensity image in ROI 1 and ROI 2, respectively; (**c,d**) Results of ship detection in image coordinates in five frames; (**e,f**) GNN data association between AIS and GF-4 detection in a single frame; (**g,h**) Point pairs after RANSAC processing; (**i,j**) Results of ship tracking in geographic coordinates using improved MHT. The average absolute error of motion estimation about ships is reported in Table 3 in detail. The tracking accuracy is accurate and improved largely after position correction with AIS data. The total location error is reduced from 3800 m to 90 m. The speed and the course are well estimated by our method, and the average error of speed and course are 0.3 kn (approximately 0.15 m/s) and 2.5\({}^{\circ}\), respectively. Meanwhile, it can also be seen from Figure 6b that the estimated accuracy of speed is improved with the increase of speed. The accuracy of motion estimation can basically meet the needs of marine surveillance, and illustrates the high-efficiency of the proposed method. The results presented in the experiment are obtained with a laptop (Intel Core i5, CPU 2.5 GHz, RAM 6 G) using MATLAB 2010a software. In each ROI, the average processing time from ship detection to ship tracking is approximately 50 s per frame, which shows that our algorithm has the potential for near real-time processing. Figure 5: Amplitude information of ships. (**a**) Amplitudes of tracked ships in five frames. Different colored lines represent different ships; (**b**) Mean amplitudes of tracked ships compared with the sizes of ships verified by AIS data. Figure 6: Comparisons of the motion estimation with AIS data. (**a**) Absolute error between estimated location and AIS location; (**b**) Estimated speed compared with AIS speed; (**c**) Estimated course compared with AIS course.