<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In order to detect non-cooperative target UAV quickly and accurately, a novel method of UAV detection method based on graph theory and HOG-FLD feature fusion is presented in this paper. In order to avoid the time-consuming full search, the candidate areas of the UAV are obtained through the selective search of the image segmentation and the similarity, and the features are extracted through the method of gradient orientation histogram fusion FLD linear to train the SVM classifier with generalization ability to identify the UAV. The method can detect the UAV quickly and accurately under complicated background and circumstances of various position and angle. Compared with the sliding window method based on image segmentation and HOG+SVM, the experimental results show that the speed of this method has been obviously improved with the same recognition accuracy.</p></abstract>

In order to detect non-cooperative target UAV quickly and accurately, a novel method of UAV detection method based on graph theory and HOG-FLD feature fusion is presented in this paper. In order to avoid the time-consuming full search, the candidate areas of the UAV are obtained through the selective search of the image segmentation and the similarity, and the features are extracted through the method of gradient orientation histogram fusion FLD linear to train the SVM classifier with generalization ability to identify the UAV. The method can detect the UAV quickly and accurately under complicated background and circumstances of various position and angle. Compared with the sliding window method based on image segmentation and HOG+SVM, the experimental results show that the speed of this method has been obviously improved with the same recognition accuracy.

Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature Fusion

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature Fusion"}

In order to detect non-cooperative target UAV quickly and accurately, a novel method of UAV detection method based on graph theory and HOG-FLD feature fusion...

Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature Fusion

Online veröffentlicht: 07. Mai 2018

Seitenbereich: 106 - 114

DOI: https://doi.org/10.21307/ijanmc-2018-020

Schlüsselwörter
Image Segmentation, Graph Theory, HOG, FLD, SVM

© 2018 Li Xiaoping et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

TABLE I.

Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature Fusion

Online veröffentlicht: 07. Mai 2018

Seitenbereich: 106 - 114

DOI: https://doi.org/10.21307/ijanmc-2018-020

SchlüsselwörterImage Segmentation, Graph Theory, HOG, FLD, SVM

© 2018 Li Xiaoping et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

TABLE I.

Schlüsselwörter
Image Segmentation, Graph Theory, HOG, FLD, SVM