Symbol recognition using a Galois lattice of frequent graphical patterns

Graphics recognition is an important task in many real-life applications. In this article, we propose a new approach to recognize graphical symbols by the use of a frequent Galois lattice. We propose to build a concept lattice not in terms of graphical patterns but in terms of frequent graphical patterns. The purpose of this paper is twofold : first, we try to identify the best primitives from a given graphical symbol based on a descriptor invariant to rotation, translation and scaling. Each symbol is decribed using a feature vector computed on stable neighborhood for a set of points chosen randomly from the symbol. Secondly, we propose a new recognition approach based on a frequent Galois lattice. The obtained concept lattice based on frequent patterns is used as a classifier. The retrieval performance and behavior of the method have been tested for graphics recognition. We have compared our method with others based on different descriptors and classifiers. Our approach proves that the symbol description method and the algorithm used to extract frequent attributes to build the frequent Galois lattice are suitable to the recognition process.