Abstract
Abstract Computerized methods have been used for structure health monitoring and defect recognition in the civil engineering field for many years. However, there are still non-uniform illumination problems that require more research efforts to resolve. In view of this, a new support-vector-machine-based rust assessment approach (SVMRA) is developed in this research for steel bridge rust recognition. SVMRA combines Fourier transform and support vector machine to provide an effective method for non-uniformly illuminated rust image recognition. After comparison with the popular simplified K-means algorithm (SKMA) and BE-ANFIS, it is shown that the proposed SVMRA performs more effectively in dealing with non-uniform illumination and rust images of red- and brown-color background over SKMA and BE-ANFIS.
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