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 |
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Appears in Collections: | Journal Article |
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