Content-based retrieval and recognition of graphic images requires good models for symbol representation, able to identify those features providing the most relevant information about the shape and the visual appearance of symbols. In this work we have used the Radon transform as the basis to extract the representation of graphic images as it permits to globally detect lineal singularities in an image, which are the most important source of information in these images. The image obtained after applying Radon transform can be used directly to describe the symbol, or can be used to extract new and compact descriptors from it, which will also be based on lineal information about the image. We present some preliminary results showing the usefulness of this representation with a set of architectural symbols.