Software designed to help identify criminals who write ransom notes, forge checks

January 23, 2001

BUFFALO, N.Y. -- Who wrote the Jon-Benet Ramsey ransom note? A computer program developed at the University at Buffalo that is 98 percent effective in determining authorship of handwritten documents soon may be able to assist in answering such questions.

In criminal cases, the question of who penned a ransom note or forged a check is solved by human handwriting analysts. But because they are human, even the best graphologists cannot claim complete objectivity.

The UB software is the first that can identify who wrote a particular document based on purely scientific criteria. "A human expert may put in his or her own bias even unconsciously," said Sargur Srihari, Ph.D., principal investigator and SUNY Distinguished Professor in the Department of Computer Science and Engineering in the College of Arts and Sciences and School of Engineering and Applied Sciences at UB.

"We have built the foundation for a handwriting analysis system that will quantify performance and increase confidence in determining a writer's identity.

"This is about validating individuality in handwriting," Srihari noted. "The idea that everyone's handwriting is different is taken for granted. What we have done is to develop purely scientific criteria for that premise."

It is the first time researchers have attempted to do that based on a large database of handwriting and by using a totally automated means of measuring specific features of human handwriting, said Srihari, who also is director of UB's Center for Document Analysis and Recognition (CEDAR).

CEDAR is the world's largest university-based research center devoted to new technologies that can recognize and read handwriting. It was CEDAR's expertise in developing systems that can read and interpret handwritten addresses on envelopes for the U.S. Postal Service that attracted interest -- and a $428,000 grant -- from the National Institute of Justice.

Providing a scientific basis for establishing the individuality of handwriting has become essential for admitting handwriting evidence in U.S. courts due to a number of recent rulings concerning expert testimony, Srihari said.

"In this project, we are developing a technology whose job it is to authenticate documents," said Srihari. The UB researchers developed the software by first collecting a database of more than 1,000 samples of handwriting from a pool of individuals representing a microcosm of the U.S. population in terms of gender, age and ethnicity.

Multiple samples of handwriting were taken from subjects, each of whom was asked to write the same series of documents in cursive.

Instead of analyzing the documents visually, the way a human expert would, Srihari explained, the researchers deconstructed each sample, extracting features from the writing, such as measuring the shapes of individual characters, descenders, and the spaces between lines and words.

The researchers then ran the samples through their software program. "We tested the program by asking it to determine which of two authors wrote a particular sample, based on measurable features," said Srihari. "The program responded correctly 98 percent of the time."

Srihari explained that human experts look for arcades and garlands, features that may distinguish one person's penmanship from another's.

The current software should be able to conduct that type of advanced analysis within the year, he added. The goal of authenticating documents in criminal cases usually is to determine whether or not a particular suspect wrote the document in question.

However, the scientific approach that Srihari and his colleagues are developing also may be useful in establishing individuality (such as with DNA, fingerprints or facial features) in the emerging field of biometrics, which is the automated identification of a person based on precise measurements of physiological or behavioral characteristics.
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Funded by the National Institute of Justice, it's the first software program designed to develop computer-assisted handwriting analysis tools for forensic applications.

University at Buffalo

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