A vector space model for automatic indexing
Communications of the ACM
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases
Defining Writer's Invariants to Adapt the Recognition Task
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Writer Identification By Writer's Invariants
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Individuality of Handwriting: A Validation Study
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Writer Identification Using Text Line Based Features
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
A Comparison of Clustering Methods for Writer Identification and Verification
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Pattern Recognition Letters
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
Identifying Join Candidates in the Cairo Genizah
International Journal of Computer Vision
Biometric recognition using online uppercase handwritten text
Pattern Recognition
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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This communication deals with the Writer Identificationtask. Our previous work has shown the interest of usingthe graphemes as features for describing the individualproperties of Handwriting. We propose here to exploit thesame feature set but using an information retrievalparadigm to describe and compare the handwritten queryto each sample of handwriting in the database. Using thistechnique the image processing stage is performed onlyonce and before the retrieval process can take place, thusleading to a significant saving in the computation of eachquery response, compared to our initial proposition. Themethod has been tested on two handwritten databases.The first one has been collected from 88 different writersat PSI Lab. while the second one contains 39 writers fromthe original correspondence of Emile Zola, a famousFrench novelist of the last 19th century. We also analyzethe proposed method when using concatenation ofgraphemes (bi and tri-gramme) as features.