Image Quality Assessment for Construction E-inspection: A Case Study

Zhiming Dong (), Weisheng Lu and Junjie Chen
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Zhiming Dong: The University of Hong Kong
Weisheng Lu: The University of Hong Kong
Junjie Chen: The University of Hong Kong

A chapter in Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate, 2023, pp 125-133 from Springer

Abstract: Abstract The E-inspection platform provides a non-physical onsite presence solution for inspectors. The supervision units can inspect the tasks by online submitted documents. The image is an essential data source on the E-inspection platform because it can provide rich and intuitive information for inspectors. However, if the quality of the submitted image is low, the uploader needs to re-upload the record for inspection, which reduces the efficiency. The image quality assessment (IQA) metric can assess image quality quantitatively. The application of the IQA metric in the E-inspection platform can help the inspection record uploader recognize the low-quality image before submission. In this research, different IQA metrics are selected and conducted in an actual E-inspection task to illustrate efficiency and effectiveness.

Keywords: Construction industry; Image quality assessment; E-inspection; Deep learning (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-981-99-3626-7_10

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