Visual search time in detection tasks with multiple targets : Considering change of the effective stimulus field area

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)328-334
Journal / PublicationInternational Journal of Industrial Ergonomics
Issue number4
Publication statusPublished - Jul 2013


Visual search tasks are of great importance in quality control to ensure that defective products do not get to the marketplace and affect the function, safety and acceptability of products. The experiment reported here was to measure visual search performance for a task involving three targets of identical difficulty. Participants were required to find all three targets. The aims were to see if search times fitted the random strategy model, and particularly, if search times for the second and third targets found would be shorter than those predicted by the current search model for multiple targets. The results showed that for both individual and pooled data the participants tended to use random search strategies thereby validating the random search model for multiple targets. However, search times for locating the second and third targets were shorter than the theoretical times estimated by the model. The reasons for the differences between the actual search times and the theoretical times were analyzed, and target independence in random visual search tasks with multiple targets was discussed. Finally, the concept of the effective stimulus field area and an improved random search performance model for multiple targets were proposed. Relevance to industry: This study investigated visual search performance for three targets and proposed an improved random search performance model for multiple targets. This model can be used to aid determination of effective and efficient stopping policies and to establish search time limits for detection tasks that involve multiple targets. © 2013 Elsevier B.V.

Research Area(s)

  • Industrial detection, Multiple targets, Random search