A set of geometrical features for writer identification
| Author | Hassane A. |
| Author | Al-Maadeed, Somaya |
| Author | Bouridane A. |
| Available date | 2022-05-19T10:23:16Z |
| Publication Date | 2012 |
| Publication Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Resource | Scopus |
| Identifier | http://dx.doi.org/10.1007/978-3-642-34500-5_69 |
| Abstract | Writer identification is an important field in the forensic document examination. We propose in this paper a set of geometrical features that makes it possible to characterize writers. They include directions, curvatures and tortuosities. We show how these features can be combined with edge based directional features as well as chain code based features. Evaluation of the method is performed on the IAM handwriting database. |
| Language | en |
| Publisher | Springer |
| Subject | Forensic Document Examination Handwriting curvatures Handwriting directions Handwriting tortuosities Writer identification Artificial intelligence Data processing |
| Type | Conference |
| Pagination | 584-591 |
| Issue Number | PART 5 |
| Volume Number | 7667 LNCS |
Files in this item
| Files | Size | Format | View |
|---|---|---|---|
|
There are no files associated with this item. |
|||
This item appears in the following Collection(s)
-
Computer Science & Engineering [2426 items ]