Name
Abstract | ||
|---|---|---|
Writer verification in forensic handwriting examination is usually performed on just a few lines of text available in both genuine and questioned documents. In such a case, the only source of information being the feature values measured on the document at hand, the large majority of the methods proposed in the realm of pattern recognition cannot be applied, as the large set of samples they require for training is not available. In this study we investigate to which extent a statistical characterization of the variability exhibited by a set of features commonly adopted by forensic handwriting examiners may provide valuable clue to weight the evidence drawn from the available data. We argue that such a characterization should be given in terms of parameters that can be directly linked to the perceived variation between documents, so as to be easy to understand and to report in courts. The results of a set of experiments show that simple statistical parameters, such as mean and standard error of the mean, may provide an effective way to establish both the reliability of a feature for the case at hand, as well as its relevance for verification. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICFHR.2016.0089 | 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) |
Keywords | Field | DocType |
writer verification,forensic handwriting examination,feature evaluation | Statistical parameter,Forensic science,Random variable,Handwriting,Realm,Computer science,Artificial intelligence,Standard error,Machine learning | Conference |
ISSN | ISBN | Citations |
2167-6445 | 978-1-5090-0982-4 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Parziale | 1 | 25 | 5.66 |
| Adolfo Santoro | 2 | 7 | 2.72 |
| Angelo Marcelli | 3 | 139 | 32.42 |