复杂动背景下的“低小慢”目标检测技术

吴言枫; 王延杰; 孙海江; 刘培勋

doi:10.3788/CO.20191204.0853

Volume 12 Issue 4

Aug. 2019

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Chinese Optics > 2019 > 12(4): 853-865.

WU Yan-feng, WANG Yan-jie, SUN Hai-jiang, LIU Pei-xun. LSS-target detection in complex sky backgrounds[J]. Chinese Optics, 2019, 12(4): 853-865. doi: 10.3788/CO.20191204.0853

Citation:

WU Yan-feng, WANG Yan-jie, SUN Hai-jiang, LIU Pei-xun. LSS-target detection in complex sky backgrounds[J]. Chinese Optics, 2019, 12(4): 853-865. doi: 10.3788/CO.20191204.0853

WU Yan-feng, WANG Yan-jie, SUN Hai-jiang, LIU Pei-xun. LSS-target detection in complex sky backgrounds[J]. Chinese Optics, 2019, 12(4): 853-865. doi: 10.3788/CO.20191204.0853

Citation:

WU Yan-feng, WANG Yan-jie, SUN Hai-jiang, LIU Pei-xun. LSS-target detection in complex sky backgrounds[J]. Chinese Optics, 2019, 12(4): 853-865. doi: 10.3788/CO.20191204.0853

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LSS-target detection in complex sky backgrounds

doi: 10.3788/CO.20191204.0853

WU Yan-feng^{1, 2
,},
WANG Yan-jie^1
,,
SUN Hai-jiang^{1
,
,},
LIU Pei-xun^1
,

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds:

the National Natural Science Foundation of China Youth Science Foundation Project 61602432

More Information

Corresponding author: SUN Hai-jiang, E-mail:sunhaijiang@126.com
Received Date: 14 Mar 2018
Rev Recd Date: 04 Apr 2018
Publish Date: 01 Aug 2019

Abstract

Abstract

In order to detect LSS(Low, Small and Slow) targets in complex sky backgrounds, we study the visual salient region characteristics of the LSS target and scan line filling algorithm and propose an adaptive real-time detection technology for LSS targets in dynamic complex backgrounds. Firstly, a saliency map is obtained based on the Luminance Contrast(LC) of the image. Secondly, the morphological gradient is used to extract the saliency feature and the seed points of the scan line filling algorithm are obtained by the three frame difference algorithm. Then, the scan line filling algorithm is used to grow the image and the foreground is segmented using the proposed adaptive double Gauss threshold segmentation algorithm. Finally, according to the change of the object's area of occupation, the center distance and the aspect ratio of the candidate target, the false targets are eliminated and detection is completed. In order to verify the effectiveness of the algorithm, 7 test groups of complex sky background video sequences are selected and compared with other excellent detection algorithms. The results show that the running time of the proposed algorithm for moving object detection is 0.040 9 s and the accuracy rate is 89.97%. When compared with other algorithms, the average running time is reduced by 0.35 s, and the average accuracy of detection is enhanced by 24.5%. The algorithm has good stability and is robust in target detection in complex backgrounds.
- computer vision,
- visual saliency,
- scan line filling,
- curve fitting,
- adaptive threshold segmentation

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References(35)

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LSS-target detection in complex sky backgrounds

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