This article describes visual functions dedicated to the extraction and recognition of visual landmarks, here planar quadrangles detected by a single camera. Landmarks are extracted among edge segments through a relaxation scheme, used to apply geometrical, topological and appearance constraints on sets of segments. Once extracted, such a landmark is characterized by invariant attributes so that recognition is made possible from a large range of viewpoints. Landmarks are represented by an icon which is built using the homography between the current viewpoint and a reference shape (a square). When detected again, the landmark is recognized by using a distance between icons. We propose a comparison of several of these metrics and an evaluation on actual and synthetic images that shows the validity of our approach. Results issued from experiments of a mobile robot navigating in an indoor environment are finally presented.