Name
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. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1066677.1066850 | SAC |
Keywords | Field | DocType |
different writer,cubic b-splines,stroke extraction,feature extraction,forensic document analysis,skeletonisation result,feature extraction algorithm,skeleton curve,new method,handwritten character skeletonisation,grayscale image,forensic analysis,human perception | Computer vision,Document analysis,Feature extraction algorithm,Handwriting,Pattern recognition,Computer science,Grapheme,Artificial intelligence,Stroke extraction,Grayscale | Conference |
ISBN | Citations | PageRank |
1-58113-964-0 | 15 | 0.79 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vladimir Pervouchine | 1 | 146 | 8.91 |
| Graham Leedham | 2 | 526 | 44.71 |
| Konstantin Melikhov | 3 | 50 | 3.74 |