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The status of the road infrastructure affects the social, economic, and political environment of a nation. Evaluation of the pavement surface condition is essential to plan timely and effective interventions. Timely actions avoid operating cost overruns, prevent uncontrolled deterioration and reduce operational and safety inconveniences. The problem raises the concern of studying alternatives to evaluate the status of pavement, for which a large number of investigations on automatic detection of surface flaws in flexible pavements through image processing techniques have been developed. . The objective of this article is to review and analyze these contributions. Based on the review, it was concluded that the performance of this type of systems is determined by two factors: data collection and processing. The analysis presented herein unfolds based on these factors. The development of systems that take advantage of the qualities of different sensors in data acquisition and that integrate the detection and classification of a variety of faults including severity data is considered opportune.

Revisión de métodos para la clasificación de fallas superficiales en pavimentos flexibles