Full Text:   <1156>

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CLC number: TP391.4

On-line Access: 2022-04-20

Received: 2020-12-12

Revision Accepted: 2022-05-04

Crosschecked: 2021-06-28

Cited: 0

Clicked: 2369

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Chun YIN

https://orcid.org/0000-0002-2852-6982

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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.4 P.571-586

http://doi.org/10.1631/FITEE.2000695


Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation


Author(s):  Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU

Affiliation(s):  School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; more

Corresponding email(s):   yinchun.86416@163.com, chunyin@uestc.edu.cn

Key Words:  Hypervelocity impact damage, Defect detection, Gaussian mixture model, Image segmentation


Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU. Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(4): 571-586.

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author="Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU",
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publisher="Zhejiang University Press & Springer",
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%T Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation
%A Xiao YANG
%A Chun YIN
%A Sara DADRAS
%A Guangyu LEI
%A Xutong TAN
%A Gen QIU
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T1 - Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation
A1 - Xiao YANG
A1 - Chun YIN
A1 - Sara DADRAS
A1 - Guangyu LEI
A1 - Xutong TAN
A1 - Gen QIU
J0 - Frontiers of Information Technology & Electronic Engineering
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DOI - 10.1631/FITEE.2000695


Abstract: 
To detect spacecraft damage caused by hypervelocity impact, we propose an advanced spacecraft defect extraction algorithm based on infrared imaging detection. The gaussian mixture model (GMM) is used to classify the temperature change characteristics in the sampled data of the infrared video stream and reconstruct the image to obtain the infrared reconstructed image (IRRI) reflecting the defect characteristics. The designed segmentation objective function is used to ensure the effectiveness of image segmentation results for noise removal and detail preservation, while taking into account the complexity of IRRI (that is, the required trade-offs are different). A multi-objective optimization algorithm is introduced to achieve balance between detail preservation and noise removal, and a multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used for optimization to ensure damage segmentation accuracy. Experimental results verify the effectiveness of the proposed algorithm.

基于双层多目标分割的超高速撞击航天器损伤红外检测算法

杨晓1,殷春1,Sara DADRAS2,雷光钰1,谭旭彤1,邱根1
1电子科技大学自动化工程学院,中国成都市,611731
2犹他州立大学电气与计算机工程系,美国犹他州,84321
摘要:针对超高速撞击引起的航天器损伤检测,提出一种先进的基于红外成像检测的航天器缺陷提取算法。采用高速混合模型对红外视频流采样数据中的温度变化特征进行分类,并重构图像,得到反映缺陷特征的红外重构图像。设计的分割目标函数用于保证图像分割结果对噪声去除和细节保留的有效性,同时考虑到红外重构图像的复杂性,即所需权衡不同。因此,引入多目标优化算法以实现细节保留和噪声去除之间的平衡,并采用基于分解的多目标进化算法(MOEA/D)进行优化,以保证损伤分割的准确性。实验结果验证了所提算法的有效性。

关键词:超高速撞击损伤;缺陷检测;高斯混合模型;图像分割

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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