Line Detection Using Ridgelets Transform for Graphic Symbol Representation

Retrieval and recognition of symbols in graphic images requires good symbol representation, able to identify those features providing the most relevant information about shape and visual appearance of symbols. In this work we have introduced Ridgelets transform as it permits to detect lineal singularities in an image, which are the most important source of information in graphic images. Sparsity is one of the most important properties of Ridgelets transform, which will permit us to extract a set of descriptors based on the angle and the distance to the origin of every straight line. We show how this representation can be normalized to make it invariant on traslation, rotation and scaling of the symbol. We present some preliminary results showing the usefulness of this representation with a set of architectural symbols.