On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
A set of handwriting families: style recognition
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Style-based retrieval for ancient Syriac manuscripts
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
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Handwriting originates from a particular copybook style such as Palmer or Zaner-Bloser that one learns in childhood. Since questioned document examination plays an important investigative and forensic role in many types of crime, it is important to develop a system that helps objectively identify a questioned document's handwriting style. We proposed a handwriting analysis system that can assist a document examiner in the identification of the writer's handwriting style and therefore of his/her origin or nationality. We collected 33 English alphabet copybook styles from 18 countries. Here, we extend the analysis using several data mining techniques to discover important information that can be gleaned from a handwriting copybook style image database, e.g., the most information- bearing alphabet characters for the purpose of copybook style identification and the relationship between geographical regions and similarity based clusters of copybook styles.