Multi-scaled and multi oriented character recognition: an original strategy
Sébastien Adam, Jean-Marc Ogier, Claude Cariou, Rémy Mullot, Joël Gardes, Y. Lecourtier · 1999
We propose an original methodology allowing detection and recognition of multi-oriented and multi-scaled shapes. The supports on which the method is applied are technical documents representing the network of the French telephonic operator (France Telecom) overlaid on urban maps. The adopted technique, based on the Mellin Fourier Transform is integrated in a global strategy that permits one to solve ambiguous situations, through the provision of contextual information. The strategy, which is applied to solve the character/symbol classification problem, can be divided into two stages. The first one consists of constructing a moment invariants vector from each shape which is extracted from a character layer issued from the system approach. The second consists of detecting and recognising connected shapes. The results of the application of this technique are very encouraging, since the classification rate reaches excellent scores if we consider that no contextual information has been integrated in the recognition process (orientation of the string, integration of data issued from dictionaries stored on alpha-numeric databases).