Corrosion is one of the major causes of the structural defects that affect vessel hulls. For its early detection, intensive inspections of the inner and outer structures of the vessel hull are carried out at a great cost, where the visual assessment plays an important role. In order to reduce the cost of the visual inspections, we present a corrosion detector to identify defective areas in digital images taken from vessel hulls. Two main contributions stand out: on the one hand, a specific detector which combines color and texture features to describe corrosion; on the other hand, a prior stage which implements a generic-defect search based on the concept of saliency, and it is used to boost the specific corrosion detector. Both the original and the saliency-boosted methods provide successful detection rates, but the guidance by means of saliency allows for precision improvements.