## 4 Experimental Results and Analysis
### Comparison of Experimental Results  
#### 4.2.1 Comparison of Experimental Results Based on Kitti Dataset  
Indicator description: RN represented the number of reference image feature points; WN: the number of image feature points to be matched; MN: the number of matching points; PT: the matching time; and rems represented the rems error. First, the Kitti dataset was used, and the feature point extraction results of a group of pictures were randomly selected for display. These included reference images and images to be registered. The serial number in the dataset was 17). The feature-point extraction results of the SIFT algorithm of the reference image and the algorithm of this paper are shown in Figure 4; the results of the SIFT algorithm of the image to be registered and the algorithm of this paper are shown in Figure 5. Of these, Figures 4a and 5a are the feature points extracted by the SIFT algorithm, and Figures 4b and 5b are those extracted by the algorithm in this paper, which increased the stability factor and simplified the description. The number of feature points obtained by the algorithm was reduced Figure 4a. The number of feature points  
Figure 3: 96-dimensional feature descriptor. extracted by the SIFT algorithm was 6203. After optimization by the algorithm in this paper, the number of feature points in Figure 4b was 4725. The number of features extracted by the SIFT algorithm in Figure 5a was 4348, and the number optimized by the algorithm in this paper was 3429. From Figures 4 and 5, the feature points extracted by the algorithm were also sparser than those of the SIFT algorithm, which proved the role of the stability factor. The matching results of the reference image and the image to be registered are shown in Figure 6, and the matching results of the SIFT algorithm are shown in Figure 6a. The matching time of the SIFT algorithm was 3.284 s with a root mean square error of 0.153. Using the feature descriptor to remove the four-corner rectangular area made the feature description ability faster and eliminated some less ideal matching point pairs. The matching results of the optimized  
Figure 5: Extraction results of feature points of the 17 th group of images to be registered. (**a**) Feature point extraction result of the SIFT algorithm; (**b**) feature point extraction result of this algorithm. Figure 6: Matching results of the 17 th group of pictures. (**a**) The matching results of the SIFT algorithm; (**b**) the matching results of the algorithm in this paper. Figure 7: _Cont._  
The specific experimental data of the kitti dataset is displayed in Table 2, and Figure 11 is a comparison diagram of the corresponding experimental results. Figure 11a,b compares the number of feature points of the reference image and the image to be compared. Compared with the SIFT algorithm, the number of feature points was greatly reduced, with an average reduction ratio of 20.4 and 19.3%, respectively. Figure 11c shows the comparison results of the image matching time, which was reduced on average by 30.0% compared with the SIFT algorithm; Figure 11d shows that the error comparison results of rems, decreased by 12.7%. The results on the Euroc dataset also demonstrated the advantages of our algorithm in matching time and error. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Number**} & \multicolumn{4}{c}{**SIFT Algorithm**} & \multicolumn{4}{c}{**The Algorithm of This Paper**} \\ \cline{2-11}  & **RN** & **WN** & **MN** & **PT(s)** & **rems** & **RN** & **WN** & **MN** & **PT(s)** & **rems** \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the results of Kitti dataset. Figure 7: Comparison of the kitti dataset’s specific experimental data in four categories. (**a**) the number of feature points of the reference image; (**b**) the number of feature points of the images to be compared; (**c**) matching time; (**d**) Rems errors. Figure 8: The extraction result of feature points of the \(11\)th reference image.