| Title |
|
Handwritten character skeletonisation for forensic document analysis |
|
|
| Publication Date |
|
| Author(s) |
|
| Type of document |
|
| Language |
|
| Entity Type |
|
| Publisher |
|
Association for Computing Machinery (ACM) |
|
|
| Place of publication |
|
New York, United States of America |
|
|
| DOI |
|
| UNE publication id |
|
| Abstract |
|
A new method of skeletonisation (stroke extraction) of handwritten character images is presented. The method has been designed to extract the skeleton which is very close to human perception of the original pen tip trajectory. The need in such skeletonisation arises from feature extraction algorithms which are sensitive to inaccuracies in positions of skeleton curves. One class of such algorithms are those for extraction of features used in forensic analysis of handwriting. The skeleton is constructed in three steps directly from the grayscale image and is represented as a set of curves, which, in turn, are represented as cubic B-splines. Such representation also eases feature extraction. Experiments have been performed on 150 images of grapheme "th" written by different writers. The assessment of the skeletonisation results are presented. |
|
|
| Link |
|
| Citation |
|
Proceedings of the 2005 ACM Symposium on Applied Computing, v.1, p. 754-758 |
|
|
| ISBN |
|
| Start page |
|
| End page |
|