Combining Matching Scores in Identification Model
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
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
Offline handwritten character recognition of Gujrati script using pattern matching
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Generation of IFS fractal images based on hidden markov model
Transactions on Edutainment VIII
Texture-based descriptors for writer identification and verification
Expert Systems with Applications: An International Journal
Offline text-independent writer identification using codebook and efficient code extraction methods
Image and Vision Computing
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In this paper, we use HMM based recognizers for the identification and verification of persons based on their handwriting. For each writer, we build an individual recognizer and train it on text lines of that writer. This gives us recognizers that are experts on the handwriting of exactly one writer. In the identification or 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 considered input. These scores are sorted and the resulting ranking is used for both identification and verification. In an identification experiment in 96.56% of all cases the writer out of a set of 100 writers is correctly identified. Second, in a verification experiment using over 8,600 text lines from 120 writers an Equal Error Rate (EER) of about 2.5% is achieved.