Past projects have used photographs to tell computers and humans apart. Examples include Carnegie Mellon's PIX CAPTCHA, Oli Warner's KittenAuth, and work done by Chew and Tygar. These projects have a common weakness: they use relatively small image databases. There's a fundamental reason for this. It's difficult for a computer to automatically classify pictures with high accuracy — that's why the task is useful as a HIP. An image database small enough to be constructed manually by a researcher is also small enough to be manually reconstructed by an attacker.
Asirra is different because of our unique partnership with Petfinder.com, the world's largest site devoted to finding homes for homeless pets. They've provided us with over three million images of cats and dogs, manually classified by people at thousands of animal shelters across the United States.