Anne-Laure Bianne-Bernard

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This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on(More)
This paper describes the system for the recognition of French handwriting submitted by A2iA to the competition organized at ICDAR2011 using the Rimes database. This system is composed of several recognizers based on three di erent recognition technologies, combined using a novel combination method. A framework for multiword recognition based on weighted(More)
This article describes the isolated word recognizer presented by the authors to the ICDAR 2009 French handwriting recognition competition. This system is a combination of three isolated word recognizers based on different features and models. A novel n-best combination method is proposed and compared to standard combination methods. New results on the ICDAR(More)
This paper presents an HMM-based recognizer for the off-line recognition of handwritten words. Word models are the concatenation of context-dependent character models (trigraphs). The trigraph models we consider are similar to triphone models in speech recognition, where a character adapts its shape according to its adjacent characters. Due to the large(More)
Recognition of handwritten characters has been a popular task for the evaluation of classification algorithms for many years. Looking at the latest results on databases such as USPS or MNIST, one could think that character recognition is a solved problem. In this paper, we claim that this is not the case for two reasons : first because the classical(More)
This paper presents an HMM-based recognizer for the off-line recognition of handwritten words. Word models are the concatenation of context-dependent character models: the trigraphs. Due to the large number of possible context-dependent models to compute, a clustering is applied on each state position, based on decision trees. Our system is shown to perform(More)
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