Work

Modélisation de HMMs en contexte avec des arbres de décision pour la reconnaissance de mots manuscrits

Year: 2010

Type: conference-paper

Abstract: 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 better than a baseline context independent system, and reaches an accuracy higher than 74% on the publicly available Rimes database.

Source: HAL

Authors: Bianne, Anne-Laure, Kermorvant, Christopher, Likforman-Sulem, Laurence

Institution: Laboratoire Traitement et Communication de l’Information

Language: French

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4321430287

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