Real-time pixel-level fusion of colour and thermal (RGB-T) imagery via extrinsic optical alignment: Scope for automating building inspections
Keywords:Building Inspection, Real-time Fault Detection, RGB-T Fusion
Building inspections and energy surveys are performed to detect and diagnose building defects, however, existing inspection methods are highly labour intensive, time consuming, and not suitable for large-scale audits. This work presents a thermal-colour fusion technique using pre-capture optical alignment that eliminates the need for compute-intensive post-processing of data. The coinciding axes of dual cameras also prevent parallax errors, which helps expand its applications to near proximity or indoor thermal inspection as well. A prototype of this design was assembled and tested, which showed a pixel-level accurate alignment of thermal and colour camera imagery with minimal computation. The research and development in this paper provides scope and feasibility to automate building inspection techniques through drone-based low-powered embedded machine learning models and identify faults in real-time for large-scale surveys of building façades.
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Copyright (c) 2022 M. H. Shariq, B. R. Hughes
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