This research paper addresses the critical issues of enhancing the metrological and cognitive efficiency of X-ray image analysis performed by human operators within the customs control framework. For the first time, X-ray inspection is theoretically substantiated as an “integrated human-machine measurement system.” A six-stage decision-making model for operators was developed based on Signal Detection Theory (SDT) and Markov stochastic chains. An experimental study involving 20 operators of various categories was conducted, analyzing a database of 500 X-ray images. The results indicate that the Probability of Detection (POD) and False Alarm Rate (FAR) are directly contingent upon cognitive workload and image complexity. The paper concludes by proposing a new conceptual model for training customs X-ray operators and offering practical recommendations for the algorithmization of the analysis process.

Customs control, X-ray inspection, human factor, Signal Detection Theory (SDT), cognitive workload, visual search, threat detection, algorithmization, metrological uncertainty, Markov chains.

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