Is your handwriting so distinctly different from anyone else's that an expert could tell whether you — and you alone — scrawled a note that you may not even remember writing?
Could a computer do the same thing by simply "looking" at a few simple features?
The answer is yes, and no one is more surprised than the computer scientist who produced the first scientific evidence that handwriting is individualistic. No one else writes exactly like you. Like your fingerprints, your handwriting is yours and yours alone.
And that's a matter of great interest to the courts.
In a key ruling in 1993, the U.S. Supreme Court established guidelines for the admissibility of scientific evidence, saying the evidence must be backed up by scientific experimentation. As a result, handwriting analysis in recent years has routinely been thrown out by the courts because no one could prove it is scientifically valid.
So the National Institute of Justice turned to Sargur Srihari, a computer scientist and director of the Center of Excellence in Document Analysis and Recognition at the University of Buffalo.
"The motivation was to establish whether everybody's handwriting is individualistic," Srihari says. "Surprisingly, this fact had not been established with scientific experimentation."
Reading Handwritten Letters
But it has now, thanks to the efforts of Srihari and several colleagues. On April 29th, the U.S. District Court for the Eastern District of Pennsylvania listened to Srihari describe the evidence his team has compiled and then allowed expert testimony concerning handwritten documents to be introduced as evidence.
Srihari says that when he first started working on the project he didn't have a clue as to whether handwriting is individualistic. But he knew something about computers, and his track record in computer analysis of handwriting is pretty impressive.
He led the university's team that began tackling a similar problem for the U.S. Postal Service more than a decade ago. Automation was the key to streamlining the postal service, but how do you automate handwritten letters? Srihari thought he could do it with a computer program, despite skepticism at the post office.
"They didn't believe it was possible," he says. Some noted that they had trouble even reading their own handwriting, so how could a computer do it?
But nobody doubts it now. The software developed in Srihari's lab is now in use at all postal centers across the country, and it can read nearly 75 percent of handwritten addresses. The rest are kicked out of the sorter and require human intervention.
But 75 percent is impressive enough to have caught the attention of the National Institute of Justice, which asked Srihari if he could use his expertise to develop a scientific basis for determining whether handwriting analysis is real or mumbo jumbo.
Marks That Mark Us
His team collected handwriting samples from 1,500 persons across the country of various ages and ethnic backgrounds.
"We tried to make it as representative [of the general population] as possible," he says.
The software developed for the post office was modified somewhat to zero in on differences in the handwriting. Such things as the spacing of letters, and how the letters are slanted, and how "loops" in numbers and letters are opened and closed, were easily recognized by the software. There is considerable variation in how hard we press down when writing, and the computer could detect that by the darkness of the letters.
The team ended up with 11 features that characterize the structure of the writing, such as the size of margins and spacing of characters and lines, and 512 features of individual letters and numbers. Two people might make an identical "e," but it is less likely the same two people would also make an identical "b," and so on.
"So we set up an experiment for our computer," Srihari says. "Could the computer program tell whether two documents were written by the same person, or two different people?"
In each case the researchers knew the answer, "and we wanted to see if the computer could figure it out also."
The results were a bit astounding. If given a substantial document, say a complete page of handwriting, the computer got it right 96 percent of the time. Even if just given a couple of words, the computer still nailed it more than 80 percent of the time.
"That's pretty high, and it's surprising because we were using pretty simple features," Srihari says.
A human, properly trained, should do even better, he adds.
There are far more sophisticated features, like style of writing and phrasing, that are much more difficult to analyze with software than the simpler features used by the researchers. Yet they are routinely used by handwriting experts.
One area that Srihari's research did not address is how hard, or easy, it might be to fool the computer, or the expert. It might not be all that difficult to trick the computer, but he suspects it would be a lot tougher to hoodwink the human expert.
A human, for example, might detect changes in writing style in a ransom note designed to disguise the identity of the writer, but still pick up individualistic features that would point to the true author.
"One could use all kinds of approaches to overcome the disguise issue," he says.
Srihari found the research quite convincing, and it is being published in the July issue of the Journal of Forensic Sciences. It won't convince everyone, of course, because some still regard handwriting analysis as akin to astrology.
And some will have ample reason to challenge the results. A criminal case could hinge upon the determination of whether a defendant really penned that ransom note, so lawyers will have much to fight about.
But so far, the findings have held up well.
"There have been a couple of federal court cases where the decision went in favor of admitting handwriting evidence" after hearing his report, Srihari says.
Maybe this is the guy we need to sic on the spammers. Surely his computer program could find out who they are, give us their home addresses, and put a few of them in jail.
Lee Dye’s column appears weekly on ABCNEWS.com. A former science writer for the Los Angeles Times, he now lives in Juneau, Alaska.