Image-processing technique to detect carbonation regions of concrete sprayed with a phenolphthalein solution

Abstract The carbonation of concrete is one of the factors influencing the durability of reinforced concrete members or structures. Manual measurements can reportedly induce low reproducibility when measuring carbonation depths. This study presents a new image-processing algorithm for the automatic detection of carbonated regions of concrete sprayed with a phenolphthalein solution. The proposed image-processing algorithm consists of a primary detection process based on binarization and a morphology analysis and a secondary detection process based on a convex hull. A series of tests of images of carbonated concrete sprayed with the phenolphthalein solution is conducted to assess the validity of the proposed image-processing algorithm. The validation test results showed that the proposed image-processing algorithm is capable of the accurate detection of carbonated concrete regions compared to direct visual inspections.

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