Study of Bomb Technician Threat Identification Performance on Degraded X-ray Images

J. Glover, Praful Gupta, N. Paulter, A. Bovik
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Abstract

Abstract Portable X-ray imaging systems are routinely used by bomb squads throughout the world to image the contents of suspicious packages and explosive devices. The images are used by bomb technicians to determine whether or not packages contain explosive devices or device components. In events of positive detection, the images are also used to understand device design and to devise countermeasures. The quality of the images is considered to be of primary importance by users and manufacturers of these systems, since it affects the ability of the users to analyze the images and to detect potential threats. As such, there exist national standards that set minimum acceptable image-quality levels for the performance of these imaging systems. An implicit assumption is that better image quality leads to better user identification of components in explosive devices and, therefore, better informed plans to render them safe. However, there is no previously published experimental work investigating this.Toward advancing progress in this direction, the authors developed the new NIST-LIVE X-ray improvised explosive device (IED) image-quality database. The database consists of: a set of pristine X-ray images of IEDs and benign objects; a larger set of distorted images of varying quality of the same objects; ground-truth IED component labels for all images; and human task-performance results locating and identifying the IED components. More than 40 trained U.S. bomb technicians were recruited to generate the human task-performance data. They use the database to show that identification probabilities for IED components are strongly correlated with image quality. They also show how the results relate to the image-quality metrics described in the current U.S. national standard for these systems, and how their results can be used to inform the development of baseline performance requirements. They expect these results to directly affect future revisions of the standard.
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炸弹技术员对退化x射线图像的威胁识别性能研究
便携式x射线成像系统经常被世界各地的拆弹小组用来对可疑包裹和爆炸装置的内容物进行成像。炸弹技术人员使用这些图像来确定包裹中是否含有爆炸装置或装置组件。在阳性检测事件中,图像也用于理解设备设计并设计对策。这些系统的用户和制造商认为图像的质量是最重要的,因为它影响用户分析图像和检测潜在威胁的能力。因此,现有的国家标准为这些成像系统的性能设定了最低可接受的图像质量水平。一个隐含的假设是,更好的图像质量导致用户更好地识别爆炸装置中的组件,从而更好地制定使其安全的知情计划。然而,之前没有发表过研究这一问题的实验工作。为了在这个方向上取得进展,作者开发了新的NIST-LIVE x射线简易爆炸装置(IED)图像质量数据库。该数据库包括:一组简易爆炸装置和良性物体的原始x射线图像;一组相同物体的不同质量的较大的扭曲图像;所有图像的真实IED组件标签;人工任务执行结果定位和识别IED组件。招募了40多名训练有素的美国炸弹技术人员来生成人类任务表现数据。他们使用数据库显示IED组件的识别概率与图像质量密切相关。他们还展示了结果如何与当前美国国家标准中描述的这些系统的图像质量指标相关联,以及他们的结果如何用于通知基线性能需求的开发。他们希望这些结果能直接影响到未来对标准的修订。
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