Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism

doi:10.1109/TIFS.2022.3154287

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	Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism
	Zhao, Cairong 2; Zhu, Liang 2; Dou, Shuguang 2; Deng, Weihong 3; Wang, Liang 1
刊名	IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
	2022
卷号	17 页码:998-1009
关键词	X-ray imaging Security Object detection Visualization Liquids Containers Inspection Object detection X-ray dataset overlap
ISSN号	1556-6013
DOI	10.1109/TIFS.2022.3154287
通讯作者	Zhao, Cairong(zhaocairong@tongji.edu.cn)
英文摘要	One of the key challenges to the X-ray security check is to detect the overlapped items in backpacks or suitcases in the X-ray images. Most existing methods improve the robustness of models to the object overlapping problem by enhancing the underlying visual information such as colors and edges. However, this strategy ignores the situations that the objects have similar visual clues as to the background, and objects overlapping each other. Since the two cases rarely appear in existing datasets, we contribute a novel dataset - Cutters and Liquid Containers X-ray Dataset (CLCXray) to complete the related research. Furthermore, we propose a novel Label-aware Mechanism (LA) to tackle the object overlapping problem. Particularly, LA establishes the associations between feature channels and different labels and adjusts the features according to the assigned labels (or pseudo labels) to help improve the prediction results. Extensive experiments demonstrate that the LA is accurate and robust to detect overlapped objects, and also validate the effectiveness and the good generalization of the LA for arbitrary state-of-the-art (SOTA) methods. Furthermore, experimental results show that the network constructed by the LA is superior to the SOTA models on OPIXray and CLCXray, especially solving the challenges of the subset of the highly overlapped objects.
资助项目	National Natural Science Foundation of China (NSFC)[62076184] ; National Natural Science Foundation of China (NSFC)[61673299] ; National Natural Science Foundation of China (NSFC)[61976160] ; National Natural Science Foundation of China (NSFC)[61906137] ; Shanghai Innovation Action Project of Science and Technology[20511100700] ; Shanghai Municipal Science and Technology Major Project[2021SHZDZX0100] ; Fundamental Research Funds for the Central Universities
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000769991900011
资助机构	National Natural Science Foundation of China (NSFC) ; Shanghai Innovation Action Project of Science and Technology ; Shanghai Municipal Science and Technology Major Project ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/48132]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Zhao, Cairong
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit NLPR, Inst Automat, Beijing 100190, Peoples R China 2.Tongji Univ, Dept Comp Sci & Technol, Shanghai 200070, Peoples R China 3.Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Pattern Recognit & Intelligent Syst Lab, Beijing 100876, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Cairong,Zhu, Liang,Dou, Shuguang,et al. Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2022,17:998-1009.
APA	Zhao, Cairong,Zhu, Liang,Dou, Shuguang,Deng, Weihong,&Wang, Liang.(2022).Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,17,998-1009.
MLA	Zhao, Cairong,et al."Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 17(2022):998-1009.