Automatic Detection and Its Applications in Infrastructure

This chapter presents the basic principles and working methods of diagnosis and new effective parameters in diagnosing failure or anomaly. It introduces various methods for automatic detection of anomalies in infrastructure, including road paving, that can be further developed for other infrastructure, such as tunnel walls, structures, dams, silos, and power plant walls. General hypotheses and rules in processing for diagnosis belong to some rules. Each method that is available for diagnosis can be considered categorized as one of the following: photometric hypotheses, geometric and photometric hypotheses, geometric hypotheses, and transform hypotheses. The chapter provides a brief introduction to each of these methods. It presents various diagnostic methods based on feature extraction and the effect of each in detecting images containing anomalies. Some of these are: wavelet method, high amplitude wavelet coefficient percentage, high‐frequency wavelet energy percentage, wavelet standard deviation, and so on.