CAPTCHA IMAGE GENERATION

• US 20100077210A1
• Filed: 09/24/2008
• Published: 03/25/2010
• Est. Priority Date: 09/24/2008
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Ravikumar, Shanmugasundaram, Broder, Andrei
• Application Number:
  US12/236,920
• Publication Number:
  US 20100077210A1
• Time in Patent Office: Days
• US Class Current: 713/168
• CPC Class Codes: G06F 18/28 Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries
• CPC Class Codes: G06F 21/46 by designing passwords or checking the strength of passwords
• CPC Class Codes: G06V 30/10 Character recognition

Abstract

Methods and systems are described for generating captchas and enlarging a core of available captchas that are hard for an automated or robotic user to crack.

Claims

1. A computer implemented method for generating a completely automated public turing test to tell computers and humans apart, comprising:

creating a first image of an alphanumeric string;

creating a randomly generated mask; and

creating a second image of the alphanumeric string by superimposing the randomly generated mask on top of the first image.

2. The method of claim 1, wherein the mask contains one pixel for each pixel of the image.

3. The method of claim 1, wherein the mask consists of transparent pixels, white pixels, and black pixels.

4. The method of claim 2, wherein a pattern of the mask is randomly generated.

5. The method of claim 1, wherein the mask comprises splotches of white and black pixels.

6. The method of claim 5, wherein a density of the splotches is appropriate so as to maintain human ability to recognize a string reproduced within the second image.

7. The method of claim 1, further comprising:

displaying the first image of the alphanumeric string to a plurality of users;

displaying the second image of the alphanumeric string to the plurality of users;

receiving responses to both the first and second images; and

monitoring the responses from the plurality of users and comparing a correct response percentage to the first image to a correct response percentage to the second image.

8. The method of claim 7, further comprising determining if the response percentage to the second image is below an acceptable threshold.

9. The method of claim 8, further comprising limiting or eliminating usage of the second image, if the response percentage is below the acceptable threshold.

10. A computer system for generating test images to tell computers and humans apart, the computer system configured to:

create a first image of an alphanumeric string;

create a randomly generated mask; and

create an additional image of the alphanumeric string by superimposing the randomly generated mask on top of the first image.

11. The computer system of claim 10, wherein the mask contains one pixel for each pixel of the first image.

12. The computer system of claim 10, wherein the mask is the same size as the first image.

13. The computer system of claim 10, wherein the mask comprises transparent pixels, white pixels, and black pixels.

14. The computer system of claim 10, wherein a pattern of the mask is randomly generated.

15. The computer system of claim 10, wherein the mask comprises splotches of white and black pixels.

16. The computer system of claim 15, wherein a density of the splotches is appropriate so as to maintain human ability to recognize a string reproduced within the additional image.