Authorship attribution is a problem with a long history and a wide range of applications. Recent works in non-traditional authorship attribution contexts demonstrate the practicality of automatic analysis of documents based on authorial style. However, such analyses are difficult to apply and few “best practices” are available. In this paper, we show how quantitative techniques based on image similarity search can be profitably exploited for revealing forgery of handwritten corpora. More in details, we explore the case where a document is represented by means of the image of the document itself. Preliminary experimental results conducted on real data demonstrate the effectiveness of the proposed approach.
Similarity-based Image Retrieval for Revealing Forgery of Handwritten Corpora / Bartolini, I. - STAMPA. - 1 - 978-989-758-118-2:(2015), pp. 104-112. (Intervento presentato al convegno 12th International Conference on Signal Processing and Multimedia Applications (SIGMAP 2105) tenutosi a Colmar, Alsace, France nel July 20-22, 2015) [10.5220/0005564401040112].
Similarity-based Image Retrieval for Revealing Forgery of Handwritten Corpora.
BARTOLINI, ILARIA
2015
Abstract
Authorship attribution is a problem with a long history and a wide range of applications. Recent works in non-traditional authorship attribution contexts demonstrate the practicality of automatic analysis of documents based on authorial style. However, such analyses are difficult to apply and few “best practices” are available. In this paper, we show how quantitative techniques based on image similarity search can be profitably exploited for revealing forgery of handwritten corpora. More in details, we explore the case where a document is represented by means of the image of the document itself. Preliminary experimental results conducted on real data demonstrate the effectiveness of the proposed approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
