2009 MRes projects
- Speech enhancement using the binary mask method and its application to law enforcement
- Can crime science tools help tackle internal child sex trafficking in the UK?
- Assessing and improving whole body scanners through public involvement
- Beyond primary transfer: The secondary transfer of geoforensic trace particulates and their dissemination within social networks
- Use of a mirror-symmetry prior in small vehicle imaging
- Predicting the position of the source of blood stains for angled impacts on fabrics and exploring the effects of surface roughness on stain characteristics
- Attention to detail predicts threat detection performance in security X-ray images
- Small vehicle inspection scanner imaging: SVXi
- An evaluation of CCTV monitoring strategies for hospital security
Attention to detail predicts threat detection performance in security X-ray images
22 February 2012
Visual checks of thousands of X-ray images are carried out on a daily basis, in the attempt to detect and confiscate items that may compromise national and international security, yet the task is a challenging one for security officers who are involved in the process as screeners and decision makers.
The probability of detecting a prohibited item in an X-ray image depends on both image-based factors (e.g. orientation of the prohibited item, degree by which other items are superimposed, number and type of irrelevant items) and individual-based factors (e.g. visual knowledge of prohibited items, motivational and attentional status, decision criteria). Furthermore, accurate detection needs to be followed by a choice on the correct course of action.
Technological improvements in imaging devices can improve the effectiveness of the screening process. However, a better understanding of individual-based factors is required to optimize human-machine interactions. In the present study we administered the Autism Quotient (AQ) questionnaire, including the Attention to Detail subscale, to 124 respondents and further tested 29 of them with a screening task on unseen small-vehicle X-ray images. Results showed that the group with higher Attention to Detail scores outperformed the group with lower Attention to Detail scores in the screening task.
This advantage emerged both in simple detection accuracy and in threat localization consistency, as high scorers’ performance was not influenced by task-irrelevant spatial compatibility between vehicle direction and response locations. We suggest that a measure of the Attention to Detail trait would help identify those individuals who are most likely to efficiently carry out the screening job, and thus enhance security strategies.