In this paper we present three classifiers used in automatic forms class identification. A first category of classifier includes the k-Nearest Neighbours (kNN) and the Multi-Layer Perceptron (MLP) classifiers. A second category corresponds to a new structural classifier based on tree comparison. On one hand, a low level information based on a pyramidal decomposition of the document image is used by the kNN and the MLP classifiers. On the other hand, a high level information represents the form content with a hierarchical structure used by the new structural classifier. Experimental results are presented. Some strategies of classifier co-operation are proposed.

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Author's BiographyAbdellatif ENNAJI has been an Associate Professor at the University of Rouen since 1993.He received a PhD degree from the University of Rouen in 1993 in the field of the cooperation in classification and neural networks for pattern recognition applications. His current research domain concerns problems with Learning, Classification, Data Analysis, and in particular, the problem of data incremental learning of neural networks. These activities are especially applied to pattern recognition problems and decision-making aid in information systems.Arnaud RIBERT received a PhD degree from the University of Rouen in 1998. His major interest was data analysis and neural networks and essentially to a distribution of classification task methodologies. He currently carries out his professional activities in an industrial company.