Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture

Gautier Bideault; Luc Mioulet; Clément Chatelain; Thierry Paquet

doi:10.1117/12.2075796

8 February 2015 Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture

Gautier Bideault, Luc Mioulet, Clément Chatelain, Thierry Paquet

Proceedings Volume 9402, Document Recognition and Retrieval XXII; 94020G (2015) https://doi.org/10.1117/12.2075796
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Gautier Bideault, Luc Mioulet, Clément Chatelain, and Thierry Paquet "Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture", Proc. SPIE 9402, Document Recognition and Retrieval XXII, 94020G (8 February 2015); https://doi.org/10.1117/12.2075796

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