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ICDAR
2009
IEEE

Recognition of Handwritten Numerical Fields in a Large Single-Writer Historical Collection

9 years 6 months ago
Recognition of Handwritten Numerical Fields in a Large Single-Writer Historical Collection
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collection. Our recognizer has the particularity that it uses morphing during training: random elastic deformations are applied to fabricate synthetic training character patterns yielding an improved final recognition performance. Two different digit recognizers are evaluated, a multilayer perceptron (MLP) and radial basis function network (RBF), by plugging them into the same left-to-right Viterbi search framework with a tree organization of the recognition lexicon. We also compare with the performance obtained when no dictionary is used to constrain the recognition results.
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where ICDAR
Authors Marius Bulacu, Axel Brink, Tijn van der Zant, Lambert Schomaker
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