Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/9256
Title: Extraction and analysis of forensic document examiner features used for writer identification
Contributor(s): Pervouchine, Vladimir (author); Leedham, Graham  (author)
Publication Date: 2007
DOI: 10.1016/j.patcog.2006.08.008
Handle Link: https://hdl.handle.net/1959.11/9256
Abstract: In this paper we present a study of structural features of handwriting extracted from three characters "d", "y", and "f" and grapheme "th". The features used are based on the standard features used by forensic document examiners. The process of feature extraction is presented along with the results. Analysis of the usefulness of features was conducted via searching the optimal feature sets using the wrapper method. A neural network was used as a classifier and a genetic algorithm was used to search for optimal feature sets. It is shown that most of the structural micro features studied, do possess discriminative power, which justifies their use in forensic analysis of handwriting. The results also show that the grapheme possessed significantly higher discriminating power than any of the three single characters studied, which supports the opinion that a character form is affected by its adjacent characters.
Publication Type: Journal Article
Source of Publication: Pattern Recognition, 40(3), p. 1004-1013
Publisher: Elsevier Ltd
Place of Publication: United Kingdom
ISSN: 1873-5142
0031-3203
Fields of Research (FoR) 2008: 080199 Artificial Intelligence and Image Processing not elsewhere classified
080104 Computer Vision
080106 Image Processing
Socio-Economic Objective (SEO) 2008: 890299 Computer Software and Services not elsewhere classified
810107 National Security
810199 Defence not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

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