Writer Identification from Gray Level Distribution
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Writer Identification based on the fractal construction of a reference base
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Writer Identification Using Edge-Based Directional Features
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Handwriting and Signature: One or Two Personality Identifiers?
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Writer Profiling Using Handwriting Copybook Styles
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Introducing a very large dataset of handwritten Farsi digits and a study on their varieties
Pattern Recognition Letters
Text-Independent Writer Identification and Verification Using Textural and Allographic Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Complete Pyramidal Geometrical Scheme for Text Based Image Description and Retrieval
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Towards robust writer verification by correcting unnatural slant
Pattern Recognition Letters
Writer identification using directional ink-trace width measurements
Pattern Recognition
Contribution to the discrimination of the medieval manuscript texts: application in the palaeography
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Online text-independent writer identification based on stroke's probability distribution function
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Understanding the consistency of users' pen and finger stroke gesture articulation
Proceedings of Graphics Interface 2013
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In this paper, we analyse the variability of handwritings. The aim is to determine what sort of observations gives a first degree of handwriting characterization before initiating a text recognition process. In the case of handwriting consisting of few words, such literal amounts on cheques, this first degree of characterization can be obtained for each word, independent of signification, by extracting the measures of some pertinent observations. Outcomes of this characterization are, to a certain extent, a distinction between significants which characterise the author and signification which is the semantic aspect. Based on an analysis of 980 different handwritten amounts, it is shown that these measures define a variability space of non-uniform density. A fuzzy partition of the set of 3788 words of the database is proposed which allows to regroup handwriting styles into a small number of specific families.