Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2018.1541150
Effective detection by fusing visible and infrared images of targets for Unmanned Surface Vehicles
Xuefeng Dai
; School of Computer and Control Engineering, Qiqihar University, Qiqihar, People’s Republic of China
Jianqi Zhao
; School of Computer and Control Engineering, Qiqihar University, Qiqihar, People’s Republic of China
Dahui Li
; School of Computer and Control Engineering, Qiqihar University, Qiqihar, People’s Republic of China
Sažetak
The research progress for Unmanned Surface Vehicle (USV) is of great significance to human offshore operations. Target detection is the foundation for USV applications. Ocean wave, frog, and illumination are the most important factors that affect exactness of target detection through visible and infrared images. This paper proposes an algorithm for weighted averaging fusion of visible/infrared images. Firstly, the visible light/infrared devices are required to collect the target
surrounding information, perform feature analysis, and complete the anti-fog and de-noising preprocessing. These operations aim at improving the accuracy of image segmentation. Secondly, feature extractions of the visible and infrared target images are performed, respectively, and the recognition of the target image is further completed. Finally, image fusion is performed by weighted averaging of the targets detected by visible light and infrared images. The fusion
uses a matching matrix to represent the similarity of the two images. When the two images are very similar, the image is fused by weighting pixels, which effectively improves the accuracy of the detection. Lots of simulations were conducted on MATLAB 2015a with a personal computer, and the results verified the success rate of target detection and recognition.
Ključne riječi
Multi-scale fractal; visible image; infrared image; target detection; fusion
Hrčak ID:
225207
URI
Datum izdavanja:
12.12.2018.
Posjeta: 1.064 *