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Yuhui Wang

at The 713th Research Institute of China Shipbuilding Industry Corp.

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Proceedings Article | 5 November 2020 Paper

An auxiliary intelligent identification system for contraband of x-ray machine

Demao Ye, Zhiyuan Li, Yuhui Wang, Shiheng Yan

Proceedings Volume 11565, 115650Y (2020) https://doi.org/10.1117/12.2579877

KEYWORDS: Inspection, X-rays, Image enhancement, Intelligence systems, Image restoration, X-ray imaging, Safety

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In the international environment of violence, terrorist attacks and illegal drug smuggling, security issues are particularly important. Many companies and institutions in the world have successively developed safety inspection equipment, among which x-ray safety inspection equipment has been widely used. In order to ensure the safety of passengers, it is necessary to be able to accurately identify the knives, guns, inflammables, explosives and other dangerous articles in the luggage package during the security check, so as to reduce the probability of danger. At present, airport security inspectors need to change for half an hour, which is hard to work and easy to miss. An assistant identification system of contraband based on yolov4 to assist the security inspector to judge the X-ray image was proposed to improve the efficiency and accuracy of security inspection identification, reduce the manual detection intervention of professional training personnel, and avoid the occurrence of missed detection and false detection. A novel data augmentation method is proposed to guarantee the performance of the system in the case of a small number of samples. The experimental results show that the system has strong robustness in different channel directions and complex scenes, the comprehensive detection rate of lighter is higher than 95%, and the recognition efficiency and accuracy are greatly improved compared with the traditional convolutional neural network(CNN).

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