Classification Method Study for Automatic Form Class Identification

Abstract : 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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Communication dans un congrès
International Conference on Pattern Recognition, 1998, Brisbane, Australia. 1, pp.926-928, 1998, 〈10.1109/ICPR.1998.711385〉
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Pierre Héroux, Sébastien Diana, Arnaud Ribert, Eric Trupin. Classification Method Study for Automatic Form Class Identification. International Conference on Pattern Recognition, 1998, Brisbane, Australia. 1, pp.926-928, 1998, 〈10.1109/ICPR.1998.711385〉. 〈hal-00601502〉

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