Individuality of handwriting
Srihari, SN
University distuinguished professor, Department of Computer Science and Engineering and Director, Center of Excellence for Document Analysis and Recognition, University at Buffalo, State University of New York, Buffalo, NY 14228.

Cha, SH
Assistant professor, Pace University, Pleasantville, NY 10570.

Arora, H
Research scientist, IBM, Endicott, NY.

Lee, S
Doctoral candidate, Department of Computer Science and Engineering, Unversity at Buffalo, State Unversity of New York, Buffalo, NY 14228.


Abstract
Motivated by several rulings in United States courts concerning expert testimony in general, and handwriting testimony in particular, we undertook a study to objectively validate the hypothesis that handwriting is individual. Handwriting samples of 1500 individuals, representative of the U.S. 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 forensic document examiners (FDEs), were used to quantitatively establish individuality by using machine learning approaches. Using global attributes of handwriting 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 FDE.

Keywords:
document analysis, feature extraction, forensic science, handwriting identification, handwriting individuality

Paper ID: JFS2001227_474

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Author Srihari SN, Cha SH, Arora H, Lee S Title Individuality of handwriting Symposium , Committee on