A writer identification system for on-line whiteboard data
Pattern Recognition
Writer identification using directional ink-trace width measurements
Pattern Recognition
Repudiation detection in handwritten documents
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
A visualization based approach for digital signature authentication
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Texture-based descriptors for writer identification and verification
Expert Systems with Applications: An International Journal
Writer identification in handwritten musical scores with bags of notes
Pattern Recognition
Offline text-independent writer identification using codebook and efficient code extraction methods
Image and Vision Computing
Identifying the writer of ancient inscriptions and Byzantine codices. A novel approach
Computer Vision and Image Understanding
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In this paper, an off-line, text independent system for writer identification and verification of handwritten text lines using Hidden Markov Model (HMM) based recognizers is presented. For each writer, an individual recognizer is built and trained on text lines of that writer. This results in a number of recognizers, each of which is an expert on the handwriting of exactly one writer. In the identification and verification phase, a text line of unknown origin is presented to each of these recognizers and each one returns a transcription that includes the log-likelihood score for the generated output. These scores are sorted and the resulting ranking is used for both identification and verification. Several confidence measures are defined on this ranking. The proposed writer identification and verification system is evaluated using different experimental setups.