The New York Times The New York Times Science December 10, 2002  

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Human or Computer? Take This Test

(Page 2 of 2)

In October Dr. Blum got his wish. Dr. Malik of Berkeley and Greg Mori, a student, devised a computer program that could crack Gimpy — both the simple version used by Yahoo and the harder one on Captcha's Web site.

Since its inception two years ago, the Captcha effort has been building. Several research teams have joined the Captcha effort, trying to make and break Captchas and even using the ideas behind Captchas for new lines of research.


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Researchers at the Palo Alto Research Center modified a program used for scanning text to create a program that could solve certain types of Yahoo-Gimpy puzzles, says Dr. Henry Baird, who was in charge of that effort. The group is also developing a new text-based Captcha called Baffletext that it hopes to license to e-commerce sites.

Inspired by the themes behind Captchas, Dr. Doug Tygar, a professor of computer science at Berkeley, and his student Monica Chew are developing alternatives to passwords that are tailored to human skills. Humans have trouble remembering long, random strings of characters, yet they excel at remembering faces and objects, noted Dr. Tygar.

Dr. Malik said he first became interested in the effort after attending a Captcha conference at the Palo Alto center in January. After he and his former student Dr. Serge Belongie, now at the University of California at San Diego, developed a new object recognition technique modeled to have some of the properties of human vision, Dr. Malik decided that Captchas were ideal for testing their method.

The Yahoo-Gimpy cracking program, written by Mr. Mori, takes a version of the easy Gimpy, a distorted word displayed in a cluttered background, and finds some points along the boundary of each letter, using standard techniques of computer vision theory.

Then, applying the Malik-Belongie method, it makes a radial chart for each point indicating where the other boundary points are in relation to it. The charts of boundary points for that letter are compared with the charts of boundary points for all 26 possible letters. The closest match is usually the correct answer.

Using various tricks to make it run faster, the program can crack an easy Gimpy puzzle in a few seconds, and it gets the right answer over 80 percent of the time.

For the harder version of Gimpy, the researchers devised a program that examines entire words instead of individual letters, so its performance is in minutes rather than seconds, and it gets the puzzle right only about a third of the time. Still, the program will need on average only three tries to get the right answer.

Dr. Malik and Mr. Mori are exploring ways of improving the performance of their program on Gimpy that will also improve their general technique of recognizing objects in a cluttered background.

"We want to keep working on this in a principled way so we can use the same technique on an outdoor scene with buildings, trees and cars," Dr. Malik said.

The general technique, he said, will have many practical applications, like automated recognition of military targets or detection of trademark infringements on the Internet.

Meanwhile, Yahoo will have to install a new Captcha that is resistant to Dr. Mori's program. This task will fall to Dr. Manber's successor, since Dr. Manber moved to a new position last month as chief algorithms officer for There, he said, he plans to continue his collaborations with academic researchers.

"I'd love to foster more cooperation between industry and academica," he said. "It's great for everybody."

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Justin Merriman for The New York Times
Man or machine? That is the question Dr. Manuel Blum has tackled by devising a series of mental puzzles. Dr. Blum, by the way, is real.

Try the tests online at The Captcha Project


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Justin Merriman for The New York Times
Manuel Blum, left, a Carnegie Mellon professor, and Luis von Ahn, a Ph.D. student, devised ways of preventing automated registrations at Web sites.

An early computer, the "mechanical mind" developed at MIT, 1927.

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