German, S and Brilakis, I and DesRoches, R (2012) Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments. Advanced Engineering Informatics, 26. pp. 846-858. ISSN 1474-0346Full text not available from this repository.
The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.
|Uncontrolled Keywords:||Spalling detection Property retrieval Post-earthquake reconnaissance Machine vision Image processing Reinforced concrete|
|Depositing User:||Cron job|
|Date Deposited:||04 Feb 2015 22:41|
|Last Modified:||05 Feb 2015 00:55|