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
Information Retrieval Based Writer Identification
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
A writer identification and verification system
Pattern Recognition Letters
Writer identification using global wavelet-based features
Neurocomputing
A set of geometrical features for writer identification
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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This work investigates the automatic reading of unconstrained omni-writer handwritten texts. It shows how to endow the reading system with adaptation faculties to each writer's handwriting. The adaptation principles are of major importance to make robust decisions when neither simple lexical nor syntactical rules can be used e.g. for free lexicon and full text recognition. The first part of this communication defines the concept of writer's invariants. In the second part we explain how the recognition system can be adapted to the current handwriting by exploiting the graphical context defined by the writer's invariants. This adaptation is guaranteed, thanks to the writer's invariants, by activating interaction links over the whole text between the recognition procedures of word entities and those of letter entities.