Writer recognition on arabic handwritten documents
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
A set of geometrical features for writer identification
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Writer identification in handwritten musical scores with bags of notes
Pattern Recognition
The 2012 music scores competitions: staff removal and writer identification
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Text-independent writer recognition using multi-script handwritten texts
Pattern Recognition Letters
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A system for writer identification based on Arabic handwritten words was built. First a database of words was gathered and used as a test base. Then, features vectors were extracted from writers’ word images. Prior to feature extraction, normalization operations were applied to a word or text line. In this research, we studied the feature extraction and recognition operations on Arabic text, on the identification rate of writers. Since there is no well known database containing Arabic handwritten words for researchers to test, we built a new database of off-line Arabic handwriting text to be used for writer identification research. The proposed database is meant to provide training and testing sets for Arabic writer identification research. Arabic handwritten words were collected from 100 writers. We evaluated the performance of edge-based directional probability distributions as features and other features in Arabic writer identification.