We describe a system that automatically identifies the script used in documents stored electronically in image form. The system can learn to distinguish any number of scripts. It develops a set of representative symbols (templates) for each script by clustering textual symbols from a set of training documents and representing each cluster by its centroid. "Textual symbols" include discrete characters in scripts such as Cyrillic, as well as adjoined characters, character fragments, and whole words in connected scripts such as Arabic. To identify a new document's script, the system compares a subset of symbols from the document to each script's templates, screening out rare or unreliable templates, and choosing the script whose templates provide the best match. Our current system, trained on thirteen scripts, correctly identifies all test documents except those printed in fonts that differ markedly from fonts in the training set.
Automatic script identification from images using cluster-based templates
Proceedings of 3rd International Conference on Document Analysis and Recognition ; 1 ; 378-381 vol.1
01.01.1995
441049 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Automatic Script Identification from Images Using Cluster-Based Templates
British Library Conference Proceedings | 1995
|Identification of different script lines from multi-script documents
British Library Online Contents | 2002
|Building an Automated Install Script for Cluster
NTRS | 2020
|Automatic Feature Selection with Applications to Script Identification of Degraded Documents
British Library Conference Proceedings | 2003
|