A Set of Handwriting Features for Use in Automated Writer Identification.
J Forensic Sci
; 62(3): 722-734, 2017 May.
Article
em En
| MEDLINE
| ID: mdl-28054339
ABSTRACT
A writer's biometric identity can be characterized through the distribution of physical feature measurements ("writer's profile"); a graph-based system that facilitates the quantification of these features is described. To accomplish this quantification, handwriting is segmented into basic graphical forms ("graphemes"), which are "skeletonized" to yield the graphical topology of the handwritten segment. The graph-based matching algorithm compares the graphemes first by their graphical topology and then by their geometric features. Graphs derived from known writers can be compared against graphs extracted from unknown writings. The process is computationally intensive and relies heavily upon statistical pattern recognition algorithms. This article focuses on the quantification of these physical features and the construction of the associated pattern recognition methods for using the features to discriminate among writers. The graph-based system described in this article has been implemented in a highly accurate and approximately language-independent biometric recognition system of writers of cursive documents.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Processamento Eletrônico de Dados
/
Escrita Manual
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article