Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (16): 74-82.DOI: 10.3778/j.issn.1002-8331.2103-0476

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Summary of Research Progress on Application of Prohibited Item Detection in X-Ray Images

LIANG Tianfen, ZHANG Nanfeng, ZHANG Yanxi, YUAN Jinhao, GAO Xiangdong   

  1. 1.School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
    2.Huangpu Customs Technical Center, Dongguan, Guangdong 523076, China
  • Online:2021-08-15 Published:2021-08-16



  1. 1.广东工业大学 机电工程学院,广州 510006
    2.黄埔海关技术中心,广东 东莞 523076


X-ray images are widely used in security inspections. At present, most of the security inspections are done manually. However, the heavy workload and work intensity of X-ray security inspections make automatic security inspections an inevitable trend. Therefore, how to automatically detect objects based on X-ray images has become a research hotspot. With the great progress of object detection based on deep learning technology, deep learning models are also widely used in X-ray image prohibited item detection for research and obtain a lot of results. In order to summarize the existing research in a comprehensive and detailed manner, this paper first introduces the characteristics of X-ray images, the traditional methods of X-ray image detection and the methods based on deep learning, then compares the detection effects of traditional methods and deep learning methods, and analyzes the current research progress of automatic security inspection. Finally, in order to provide reference for the research of X-ray image prohibited item detection, this paper points out the research directions worthy of attention in the future.

Key words: X-ray image, prohibited item detection, object detection, deep learning



关键词: X光图像, 违禁品检测, 目标检测, 深度学习