Abstract
Computerized intelligent systems can simulate human expertise as well as analyze and process vast amounts of data instantaneously. This paper presents a hybrid intelligent computerized model for constructed facilities surface quality assessment. The model uses computers to analyze digital images of the areas to be assessed to identify and measure defects. Moreover, neural networks are used to train the system to automate the process and replicate the experts' knowledge in identifying the defects. Most techniques, currently used in construction quality assessment, rely mostly on subjective criteria. The model applies digital image processing and neural network techniques for constructed facilities surface quality assessment to make the process objective, quantitative, consistent, and reliable. Highway steel bridge coating assessment was used to exemplify the generic model.
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