Affiliations: [a] Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, China
| [b] Beijing Key Laboratory on Nuclear Detection and Measurement Technology, Beijing, China
| [c] Chinese Academy of Customs Administration, Qinhuangdao, Hebei, China
| [d] School of Vehicle and Energy, Yanshan University, Qinhuangdao, Hebei, China
Correspondence:
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Corresponding author: Zhifang Wu, Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, China. E-mail: zhifang.wu@tsinghua.edu.cn.
Abstract: BACKGROUND:X-ray imaging plays an important role in security inspection. However, the objects are complex, which makes it difficult to automatically detect prohibited and restricted objects. OBJECTIVE:This study aims to develop and test a detection method based on a new image segmentation scheme to solve the problem of detecting prohibited and restricted objects from pseudo-color X-ray images with complex backgrounds. METHODS:The internal mechanism of the influence of different color spaces on image segmentation effect is explored, and the color space component Hi is studied. Furthermore, the mechanism of the new Hi component and the influence law of its adjustable coefficient are revealed. Additionally, a detection method based on Hi color space segmentation for pseudo-color X-ray images is proposed. The segmentation and detection methods are then tested on actual X-ray images. RESULTS:The results show that hue has the greatest influence on image segmentation effect of the pseudo-color X-ray images. For different pseudo-color X-ray images with complex backgrounds, applying the proposed new Hi color space segmentation method achieves overall accuracy of 0.974 and 1.0 in detecting the gun and knife, respectively. CONCLUSION:The new X-ray image detection method based on the Hi color space segmentation proposed in this paper enables to better solve the complex background problem including object overlap and adhesion and thus more effectively meet the requirements of actual security inspection.
