How Realistic Is Threat Image Projection for X-ray Baggage Screening?

At airports, security officers (screeners) inspect X-ray images of passenger baggage in order to prevent threat items (bombs, guns, knives, etc.) from being brought onto an aircraft. Because threat items rarely occur, many airports use a threat-image-projection (TIP) system, which projects pre-recorded X-ray images of threat items onto some of the X-ray baggage images in order to improve the threat detection of screeners. TIP is regulatorily mandated in many countries and is also used to identify officers with insufficient threat-detection performance. However, TIP images sometimes look unrealistic because of artifacts and unrealistic scenarios, which could reduce the efficacy of TIP. Screeners rated a representative sample of TIP images regarding artifacts identified in a pre-study. We also evaluated whether specific image characteristics affect the occurrence rate of artifacts. 24% of the TIP images were rated to display artifacts and 26% to depict unrealistic scenarios, with 34% showing at least one of the two. With two-thirds of the TIP images having been perceived as realistic, we argue that TIP still serves its purpose, but artifacts and unrealistic scenarios should be reduced. Recommendations on how to improve the efficacy of TIP by considering image characteristics are provided.

Traditional Visual Search vs. X-Ray Image Inspection in Students and Professionals: Are the Same Visual-Cognitive Abilities Needed?

The act of looking for targets amongst an array of distractors is a cognitive task that has been studied extensively over many decades and has many real-world applications. Research shows that specific visual-cognitive abilities are needed to efficiently and effectively locate a target among distractors. It is, however, not always clear whether the results from traditional, simplified visual search tasks conducted by students will extrapolate to an applied inspection tasks in which professionals search for targets that are more complex, ambiguous, and less salient. More concretely, there are several potential challenges when interpreting traditional visual search results in terms of their implications for the X-ray image inspection task. In this study, we tested whether a theoretical intelligence model with known facets of visual-cognitive abilities (visual processing Gv, short-term memory Gsm, and processing speed Gs) can predict performance in both a traditional visual search task and an X-ray image inspection task in both students and professionals. Results showed that visual search ability as measured with a traditional visual search task is not comparable to an applied X-ray image inspection task. Even though both tasks require aspects of the same visual-cognitive abilities, the overlap between the tasks was small. We concluded that different aspects of visual-cognitive abilities predict performance on the measured tasks. Furthermore, although our tested populations were comparable in terms of performance predictors based on visual-cognitive abilities, professionals outperformed students on an applied X-ray image inspection task. Hence, inferences from our research questions have to be treated with caution, because the comparability of the two populations depends on the task.

Detection measures for visual inspection of X-ray images of passenger baggage.

In visual inspection tasks, such as airport security and medical screening, researchers often use the detection measures d' or A' to analyze detection performance independent of response tendency. However, recent studies that manipulated the frequency of targets (target prevalence) indicate that da with a slope parameter of 0.6 is more valid for such tasks than d' or A'. We investigated the validity of detection measures (d', A', and da) using two experiments. In the first experiment, 31 security officers completed a simulated X-ray baggage inspection task while response tendency was manipulated directly through instruction. The participants knew half of the prohibited items used in the study from training, whereas the other half were novel, thereby establishing two levels of task difficulty. The results demonstrated that for both levels, d' and A' decreased when the criterion became more liberal, whereas da with a slope parameter of 0.6 remained constant. Eye-tracking data indicated that manipulating response tendency affected the decision component of the inspection task rather than search errors. In the second experiment, 124 security officers completed another simulated X-ray baggage inspection task. Receiver operating characteristic (ROC) curves based on confidence ratings provided further support for da, and the estimated slope parameter was 0.5. Consistent with previous findings, our results imply that d' and A' are not valid measures of detection performance in X-ray image inspection. We recommend always calculating da with a slope parameter of 0.5 in addition to d' to avoid potentially wrong conclusions if ROC curves are not available.

Automation in airport security X-ray screening of cabin baggage: Examining benefits and possible implementations of automated explosives detection.

Bomb attacks on civil aviation make detecting improvised explosive devices and explosive material in passenger baggage a major concern. In the last few years, explosive detection systems for cabin baggage screening (EDSCB) have become available. Although used by a number of airports, most countries have not yet implemented these systems on a wide scale. We investigated the benefits of EDSCB with two different levels of automation currently being discussed by regulators and airport operators: automation as a diagnostic aid with an on-screen alarm resolution by the airport security officer (screener) or EDSCB with an automated decision by the machine. The two experiments reported here tested and compared both scenarios and a condition without automation as baseline. Participants were screeners at two international airports who differed in both years of work experience and familiarity with automation aids. Results showed that experienced screeners were good at detecting improvised explosive devices even without EDSCB. EDSCB increased only their detection of bare explosives. In contrast, screeners with less experience (tenure < 1 year) benefitted substantially from EDSCB in detecting both improvised explosive devices and bare explosives. A comparison of all three conditions showed that automated decision provided better human-machine detection performance than on-screen alarm resolution and no automation. This came at the cost of slightly higher false alarm rates on the human-machine system level, which would still be acceptable from an operational point of view. Results indicate that a wide-scale implementation of EDSCB would increase the detection of explosives in passenger bags and automated decision instead of automation as diagnostic aid with on screen alarm resolution should be considered.