Abstract
In this paper we present a study of 25 structural micro features of handwriting extracted automatically from images of grapheme 'th'. The study was carried out on a total of 3823 samples collected from 165 different writers, between 15 and 27 samples per writer. The methods of feature extraction are presented along with the results. We present a direct analysis of the feature usefulness. A measure of usefulness specific to handwriting examination was designed and the usefulness of the features was estimated. It was shown that most of the extracted micro features of 'th' do possess discriminative power. Ranking of features allows simple comparison of their discriminative power.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Third International Symposium on Information Assurance and Security |
| Editors | Ning Zhang, Ajith Abraham, Qi Shi, Johnson Thomas, Patrick Kellenberger |
| Place of Publication | Los Alamitos, United States of America |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 417-422 |
| ISBN (Print) | 0769528767, 9780769528762 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | IAS 2007: 3rd International Symposium on Information Assurance and Security - Manchester, United Kingdom Duration: 29 Aug 2007 → 31 Aug 2007 |
Conference
| Conference | IAS 2007: 3rd International Symposium on Information Assurance and Security |
|---|---|
| City | Manchester, United Kingdom |
| Period | 29/08/07 → 31/08/07 |
Keywords
- Computer Vision
- Image Processing
- Pattern Recognition and Data Mining
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