By Topic

Impact of Alphabet Knowledge on Online Writer Identification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Guo Xian Tan ; Nanyang Technol. Univ., Singapore, Singapore ; Christian Viard-Gaudin ; Alex C. Kot

Character prototype approaches for writer identification produces a consistent set of templates that are used to model the handwriting styles of writers, thereby allowing high accuracies to be attained. This paper extends such work on writer identification by investigating the usage of alphabet knowledge derived from the character prototypes. In addition, we demonstrate the concept of discriminative power of alphabets. It is not unconceivable that certain alphabets allow writers to express their individuality of handwriting with a more distinct and unique style compared with other alphabets. This paper establishes that such alphabets have higher discriminative powers in identifying writers. Experiments related to the reduction in dimensionality of the writer identification system are also reported. Our results show that the discriminative power of alphabet can be used to reduce the complexity while maintaining the same level of performance for the writer identification system.

Published in:

2009 10th International Conference on Document Analysis and Recognition

Date of Conference:

26-29 July 2009