ImprovingWriter Identification by Means of Feature Selection and Extraction
ICDAR '05 Proceedings of the Eighth 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
A segmentation-free biometric writer verification method based on continuous dynamic programming
Pattern Recognition Letters
Pattern Recognition Letters
A writer identification system for on-line whiteboard data
Pattern Recognition
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Identifying the writer of ancient inscriptions and Byzantine codices. A novel approach
Computer Vision and Image Understanding
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This communication deals with the writer verification task. This task consists in deciding whether two handwritten samples have been written by the same writer or not. Handwritings are first characterized by the graphemes that have been segmented by a segmentation procedure. Handwritten samples are then analysed according to two different procedures. Text samples are described in a feature space common to the two writers. The statistic of a mutual information criteria allows to build a robust hypothesis test. In the case of small samples of handwritings such as single words, the levenstein distance is used to build a second hypothesis test. The two appoaches are evaluated on PSI database as well as the IAM database.