An AdaBoost-based approach for coating breakdown detection in metallic surfaces

Vessel maintenance entails periodic visual inspections of internal and external parts of the vessel hull in order to detect structural failures. Typically, this is done by trained surveyors at great cost. Clearly, assisting them during the inspection process by means of a fleet of robots capable of defect detection would decrease the inspection cost. In this paper, a novel algorithm for visual detection of coating breakdown is presented. The algorithm is based on an AdaBoost scheme to combine multiple weak classifiers based on Laws´ texture energy filter responses. After a number of enhancements, the method has proved successful, while the execution times remain contained.