There is a growing need for efficient visual information retrieval systems which take into account particular features of images, in order to avoid nonsense results. In this paper we propose a new method for content-based image retrieval, which can be divided into two main parts. 1) Automatic segmentation and extraction of shapes from image sub-regions. 2) Ontological descriptions of shapes contained in images. Our method allows users to perform sketch queries; these are simple drawings which represent the main idea of something the user is expecting to retrieve from the results. Once the user introduces a sketch, it is simplified using discrete curve evolution, then, it is turned into a tangent space representation. Similarity measures based on turning functions are used to recover similar images. An ontology reduces the proportion of non-sense results since the ontology permits the recovery of images related semantically, even if they do not have similar shapes