Khan, Wasiq ORCID: 0000-0002-7511-3873, Ansell, Darren ORCID: 0000-0003-2818-3315, Kuru, Kaya ORCID: 0000-0002-4279-4166 and Amina, Mahd (2016) Automated Aircraft Instrument Reading Using Real Time Video Analysis. In: 8th IEEE International Conference on Intelligent Systems IS’16, 4-6 September 2016, Sofia, Bulgaria. (Unpublished)
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Abstract
Automated Dial Reading (ADR) using image processing is a challenging task that has to deal with the dynamics of real time environment. Literature contains limited research work for ADR that is based on background subtraction, object tracking, and pattern recognition. These methods suffer from dynamic environment such as: varying light intensity, poor resolution, and vibrations in capturing device. A valuable contribution to the existing dial reading approaches is made in this paper by deploying convolution method which plays a significant role in needle/hand recognition within a dial. Proposed dial reading approach is successfully used and tested reading analogue aircraft instruments facilitated by the Flight Guardian (FG) project for automated reading of the cockpit devices in dynamic environments. Performance is evaluated by statistical analysis of the experimental results that proved the robustness of the proposed method.
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