Graph Similarity Features for HMM-Based Handwriting Recognition in Historical Documents

Abstract

Automatic transcription of historical documents is vital for the creation of digital libraries. In this paper we propose graph similarity features as a novel descriptor for handwriting recognition in historical documents based on Hidden Markov Models. Using a structural graph-based representation of text images, a sequence of graph similarity features is… (More)
DOI: 10.1109/ICFHR.2010.47

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Citations per Year

Citation Velocity: 12

Averaging 12 citations per year over the last 3 years.

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