Information Retrieval Based Writer Identification
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Text-Independent Writer Identification and Verification Using Textural and Allographic Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
A writer identification system for on-line whiteboard data
Pattern Recognition
Writer identification using global wavelet-based features
Neurocomputing
Embedded scale united moment invariant for identification of handwriting individuality
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
A visualization based approach for digital signature authentication
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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This communication deals with the problem of writer identification. If the assumption of writing individuality is true then graphical fragments that constitute it should be individual too. Therefore we propose a morphological grapheme based analysis to make writer identification.Template Matching is the core of the approach. The redundancy of the individual patterns in a writing, defined as the writer's invariants, allows to compress the handwritten texts while maintaining good identification performance. Two series of tests are reported. The first series is designed to evaluate the relevance of our approach of identification on a basis of 88 writers by evaluating the influence of the text representation (with or without invariants) on the quality of the method. The method gives about 97.7% of correct identification when using large compressed samples of handwriting. The second series of tests is designed to evaluate theinfluence of the sample size of the writing to be identified on the quality of the method. It is shown that writer identification can reach a correct identification rate of 92.9% using only samples of 50 graphemes of each writing.