Abstract
Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on contour features operating in identification mode (one-to-many) and working at the level of isolated characters. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowercase and uppercase letters), being the particular setup used by the forensic laboratory participating in this work. Three different scenarios for identity modeling are proposed, making use to a different degree of the class information provided by the alphanumeric samples. Results obtained on a database of 30 writers from real forensic documents show that the character class information given by the manual analysis provides a valuable source of improvement, justifying the significant amount of time spent in manual segmentation and labeling by the forensic specialist.
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Alonso-Fernandez, F., Fierrez, J., Galbally, J., Ortega-Garcia, J. (2011). Exploiting Character Class Information in Forensic Writer Identification. In: Sako, H., Franke, K.Y., Saitoh, S. (eds) Computational Forensics. IWCF 2010. Lecture Notes in Computer Science, vol 6540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19376-7_3
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DOI: https://doi.org/10.1007/978-3-642-19376-7_3
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