The process involves a computer asking a user to complete a simple test which generated by computer. Because other computers are unable to solve the CAPTCHA, any user entering a correct solution is presumed to be human.Sometimes it is described as a reverse Turing test, because it is done by a machine and targeted to a human.

You've probably seen them when you’re in internet. It is colorful images with distorted text at the bottom of Web registration forms. CAPTCHAs are used by many websites to prevent abuse from automated programs usually written to generate spam. No computer program can read distorted text as well as humans can, so bots (automated programs) cannot navigate sites protected by CAPTCHAs.

About 200 million CAPTCHAs are solved by humans around the world every day. In each case, roughly ten seconds of human time are being spent. Individually, that's not a lot of time,

What if we could make positive use of this human effort? reCAPTCHA does exactly that by channeling the effort spent solving CAPTCHAs online into "reading" books.

To archive human knowledge and to make information more accessible to the world, multiple projects are currently digitizing physical books that were written before the computer age. The book pages are being photographically scanned, and then transformed into text using "Optical Character Recognition" (OCR). The transformation into text is useful because scanning a book produces images, which are difficult to store on small devices, expensive to download, and cannot be searched. The problem is that OCR is not perfect.reCAPTCHA improves the process of digitizing books by sending words that cannot be read by computers to the Web in the form of CAPTCHAs for humans to decipher. More specifically, each word that cannot be read correctly by OCR is placed on an image and used as a CAPTCHA. This is possible because most OCR programs alert you when a word cannot be read correctly.

But if a computer can't read such a CAPTCHA, how does the system know the correct answer to the puzzle? Here's how: Each new word that cannot be read correctly by OCR is given to a user in conjunction with another word for which the answer is already known. The user is then asked to read both words. If they solve the one for which the answer is known, the system assumes their answer is correct for the new one. The system then gives the new image to a number of other people to determine, with higher confidence, whether the original answer was correct.

In My next post I will say how to use it,