This letter, addressed to the analysis of remote sensing (RS) images of the sea-surface temperature (SST) off the Portugal coast, presents a novel approach to automatically detect and characterizemesoscaleeddy-relatedstructures. The complexity of this task is due to the dynamics of the investigated region, where upwelling currents and bathymetry effects produce countless and highly heterogeneous SSTpatterns, features of interest may have smooth boundaries, and edges associated to strong temperature gradients may not correspond to any eddy. All these limit the effectiveness of an image processing based on edge features (which can be successfully applied to automatically detect eddies in other oceanographic areas, for instance, close to the Gulf Stream). The proposed scheme exploits theiso-SSTpatternsassociated to theeddy-relatedstructure to code with a rule-based definition the process that allows for their visual identification. In practice, this enables revealing various morphological parameters of theeddy-relatedstructure (i.e., the location, scale, symmetry, and rotation) and supports the exploitation of SST data allowing for annotating the RS image and benchmarking the subjectivity of the visual survey.