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Proceedings Paper

Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture
Author(s): Gautier Bideault; Luc Mioulet; Clément Chatelain; Thierry Paquet
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Paper Abstract

In this article, we propose a hybrid model for spotting words and regular expressions (REGEX) in handwritten documents. The model is made of the state-of-the-art BLSTM (Bidirectional Long Short Time Memory) neural network for recognizing and segmenting characters, coupled with a HMM to build line models able to spot the desired sequences. Experiments on the Rimes database show very promising results.

Paper Details

Date Published: 8 February 2015
PDF: 11 pages
Proc. SPIE 9402, Document Recognition and Retrieval XXII, 94020G (8 February 2015); doi: 10.1117/12.2075796
Show Author Affiliations
Gautier Bideault, Univ. de Rouen (France)
Luc Mioulet, Univ. de Rouen (France)
Clément Chatelain, Institut National des Sciences Appliquées de Rouen (France)
Thierry Paquet, Univ. de Rouen (France)


Published in SPIE Proceedings Vol. 9402:
Document Recognition and Retrieval XXII
Eric K. Ringger; Bart Lamiroy, Editor(s)

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