Recently developed spatial and spatio-temporal model checking techniques have a wide range of application domains, among which large scale distributed systems as well as signal and image analysis. In the latter domain, automatic and semi-automatic contouring in Medical Imaging has shown to be a very promising and versatile application. In the present paper we address the contouring of 2D images of nevi. One of the challenges of contouring nevi is that they show considerable inhomogeneity in shape, colour, texture and size. In addition, these images often include also extraneous elements such as hairs, patches and rulers. To deal with these challenges we explore the use of a texture similarity operator in combination with spatial logic operators. We investigate the feasibility of this technique on dermoscopic images of a large public database. To that purpose, we compare our segmentation results with the ground truth segmentation provided by domain experts; the results are very promising, both from the quality and from the performance point of view.