Web services are often protected with a challenge that's supposed to be easy for people to solve, but difficult for computers. Such a challenge is often called a CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) or HIP (Human Interactive Proof). HIPs are used for many purposes, such as to reduce email and blog spam and prevent brute-force attacks on web site passwords.

Asirra (Animal Species Image Recognition for Restricting Access) is a HIP that works by asking users to identify photographs of cats and dogs. This task is difficult for computers, but studies have shown that people can accomplish it quickly and accurately.

While random guessing is the easiest form of attack, various forms of image recognition can allow an attacker to make guesses that are better than random. There is enormous diversity in the photo database (a wide variety of backgrounds, angles, poses, lighting, etc.), making accurate automatic classification difficult.

In this project we will develop and implement an application.

1. Supervisor:
   Elad Osherov
   04-8295741
   Email: eladosherov@yahoo.com
   
2. Field:
   Computer Vision
3. Requirements:
   046195 Intro to machine learning or an equivalent course
   046746 Computer vision algorithms and applications or an equivalent course
   Or a good knowledge in these topics
   
4. Project status:
   Taken by the students Hilla Menahem and Michael Barzelai
   
5. Visit:
   Project web site