Two-channel model based adaptive schlieren detection algorithm for BOS system

doi:10.21629/JSEE.2019.02.04

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (2): 251-258.doi: 10.21629/JSEE.2019.02.04

• Electronics Technology • Previous Articles Next Articles

Two-channel model based adaptive schlieren detection algorithm for BOS system

Han LIU¹(), Yanmei ZHANG^1,*(), Baojun ZHAO¹(), Haichao GUO²(), Boya ZHAO¹()

¹ School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
² National Key Laboratory of Science and Technology on Space Microwave, China Academy of Space Technology, Xi'an 710100, China

Received:2018-03-16 Online:2019-04-01 Published:2019-04-28
Contact: Yanmei ZHANG E-mail:3120140335@bit.edu.com;0726zym@bit.edu.cn;zbj@bit.edu.cn;haizi0919@163.com;zhaoboya@bit.edu.cn
About author:LIU Han was born in 1989. She received her B.S. degree from University of Sussex at the United Kingdom in 2013. Currently, she is pursuing the Ph.D. degree at the School of Electrical and Information Engineering, Beijing Institute of Technology. Her research interests include BOS system, object detection, and flow field visualization. E-mail:3120140335@bit.edu.com|ZHANG Yanmei was born in 1967. She received her Ph.D. degree in electromechanical engineering from Beijing Institute of Technology in 2010. Since 1995, she has worked in Beijing Institute of Technology as a professor and a Ph.D. supervisor. Her interests include laser detection, BOS system, and compressed sensing. E-mail:0726zym@bit.edu.cn|ZHAO Baojun was born in 1960. He received his Ph.D. degree in electromagnetic measurement technology and equipment from Harbin Institute of Technology in 1996. From 1996 to 1998, he was a postdoctoral fellow at Beijing Institute of Technology. His main research interests include image/video coding, image recognition, infrared/laser signal processing, and parallel signal processing. E-mail:zbj@bit.edu.cn|GUO Haichao was born in 1983. He received his B.S. degree in optical engineering from University of Electronic Science and Technology in 2006. From 2009 till now, he studies satellite free space coherent optical communication and laser imaging in National key Laboratory of Science and Technology on Space Microwave and the School of Information and Electronics of Beijing Institute of Technology School. E-mail:haizi0919@163.com|ZHAO Boya was born in 1990. He received his B.S. degree from the School of Electrical Engineering and Information, Hebei University of Technology, Tianjin, China, in 2013. He is currently pursuing his Ph.D. degree at the School of Information and Electronics, Beijing Institute of Technology, Beijing, China. His current research interests include object detection, object tracking and machine learning. E-mail:zhaoboya@bit.edu.cn

Abstract

Abstract:

A schlieren detection algorithm is proposed for the ground-to-air background oriented schlieren (BOS) system to achieve high-speed airplane shock waves visualization. The proposed method consists of three steps. Firstly, image registration is incorporated for reducing errors caused by the camera motion. Then, the background subtraction dual-model single Gaussian model (BS-DSGM) is proposed to build a precise background model. The BS-DSGM could prevent the background model from being contaminated by the shock waves. Finally, the twodimensional orthogonal discrete wavelet transformation is used to extract schlieren information and averaging schlieren data. Experimental results show our proposed algorithm is able to detect the aircraft in-flight and to extract the schlieren information. The precision of schlieren detection algorithm is 0.96. Three image quality evaluation indices are chosen for quantitative analysis of the shock waves visualization. The white Gaussian noise is added in the frames to validate the robustness of the proposed algorithm. Moreover, we adopt two times and four times down sampling to simulate different imaging distances for revealing how the imaging distance affects the schlieren information in the BOS system.

Key words: background model, background oriented schlieren (BOS), schlieren detection, wavelet decomposition

Han LIU, Yanmei ZHANG, Baojun ZHAO, Haichao GUO, Boya ZHAO. Two-channel model based adaptive schlieren detection algorithm for BOS system[J]. Journal of Systems Engineering and Electronics, 2019, 30(2): 251-258.

Figures/Tables 9

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References 23

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	Actual object	Non-object
Detected	$TP$	$FP$
Not detected	$FN$	$TN$

Method	BS-DSGM	Cross correlation [3]	Optical flow [4]
MSE	100	400	320
PSNR/dB	29	15	17
SSIM	0.72	0.33	0.42

Video	SSIM
Original video	0.72	0.68	0.69	0.71
Two times down sampling video	0.60	0.58	0.59	0.57
Four times down sampling video	0.49	0.47	0.50	0.44

[1]	Li Zhihua, Zhou Fan, Tian Xiang & Chen Yaowu. High efficient moving object extraction and classification in traffic video surveillance [J]. Journal of Systems Engineering and Electronics, 2009, 20(4): 858-868.
[2]	Zha Yufei & Bi Duyan. Adaptive learning algorithm based on mixture Gaussian background [J]. Journal of Systems Engineering and Electronics, 2007, 18(2): 369-376.
[3]	Wei Zhiqiang, Ji Xiaopeng & Wang Peng. Real-time moving object detection for video monitoring systems [J]. Journal of Systems Engineering and Electronics, 2006, 17(4): 731-736.

Two-channel model based adaptive schlieren detection algorithm for BOS system

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