18 December 2001 Discriminatory power of handwriting
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Proceedings Volume 4670, Document Recognition and Retrieval IX; (2001); doi: 10.1117/12.450722
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
A study was undertaken to determine the power of handwriting to distinguish between individuals. Handwriting samples of one thousand five hundred individuals, representative of the US population with respect to gender, age, ethnic groups, etc., were obtained. Analyzing differences in handwriting was done by using computer algorithms for extracting features from scanned images of handwriting. Attributes characteristic of the handwriting were obtained, e.g., line separation, slant, character shapes, etc. These attributes, which are a subset of attributes used by expert document examiners, were used to quantitatively establish individuality by using machine learning approaches. Using global attributes of hadwriting and very few characters in the writing, the ability to determine the writer with a high degree of confidence was established. The work is a step towards providing scientific support for admitting handwriting evidence in court. The mathematical approach and the resulting software also have the promise of aiding the expert document examiner.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sargur N. Srihari, Sung-Hyuk Cha, Sangjik Lee, "Discriminatory power of handwriting", Proc. SPIE 4670, Document Recognition and Retrieval IX, (18 December 2001); doi: 10.1117/12.450722; https://doi.org/10.1117/12.450722
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KEYWORDS
Feature extraction

Image segmentation

Error analysis

Statistical modeling

Forensic science

Binary data

Statistical analysis

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