Abstract
This paper presents a new system for handwriting documents denoising and indexing. This work is based on the Hermite Transform, which is a polynomial transform and a good model of the human visual system (HVS). We use this transformation to decompose handwriting documents into local frequencies and using this decomposition, we analyze the visual aspect of handwritings to compute similarity measures. A direct application is the management of document databases, allowing to find documents coming from the same author or to classify documents containing handwritings that have similar visual aspect. Moreover, ancient documents can contain degradations from different origins. It is often necessary to clean the backgrounds of those degraded documents before analysing them. The current results are very promising and show that it is possible to characterize handwritten drawings without any a priori graphemes segmentation.
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© 2005 Springer-Verlag Berlin Heidelberg
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Bres, S., Eglin, V., Rivero, C. (2005). Handwriting Documents Denoising and Indexing Using Hermite Transform. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Data Mining. ICAPR 2005. Lecture Notes in Computer Science, vol 3686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551188_73
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DOI: https://doi.org/10.1007/11551188_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28757-5
Online ISBN: 978-3-540-28758-2
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