Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6695657 | Automation in Construction | 2018 | 10 Pages |
Abstract
ANNRI integrates the root-mean-square standard deviation (RMSSTD) and artificial neural network (ANN) to cluster a rust image based on its rust intensity or rusting severity. RMSSTD measures the similarity of rust colors on a rust image, and an ANN trained with the results of a human visual rust inspection experiment would generate the optimal number of clusters for rust intensity recognition. Together with a pre-defined rust color spectrum, ANNRI is able to perform human-visual-perception-like rust intensity recognition and screen out background noises. According to the experiments conducted in this study, the proposed ANNRI can discriminate rust intensity much better than the existing methods with a fixed number of clusters.
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Civil and Structural Engineering
Authors
Heng-Kuang Shen, Po-Han Chen, Luh-Maan Chang,