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Method for Encrypting Data in a Digital Picture Disclosure Number: IPCOM000019999D
Original Publication Date: 2003-Oct-16
Included in the Prior Art Database: 2003-Oct-16
Document File: 2 page(s) / 18K

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Data encryption is becoming an ever more important aspect of the world in which we live. Business, government, and military requirements continue to increase. Most of the concepts surrounding encryption involve taking the data, encrypting it, and allowing others to understand that the data has been encrypted and then trying to break the encryption (if desired).

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 54% of the total text.

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Method for Encrypting Data in a Digital Picture

It is very easy today to take a digital picture and extract a certain color spectrum from it. For example, in the pictures shown below, the first picture is an original color picture, and the second is a black-and-white extract from the picture. (The same could be done for other colors.)

Focusing on the black-and-white extract, you can "map" a set of matrices over the picture, with each matrix containing one "code" for a given character in the alphabet.

To set this up, I can use a total of 30 alpha-numeric characters from the ASCII table and effectively communicate anything I want. I simply need the 26 letters of the alphabet (i.e., all caps), a "space," a "question mark," a "period," and possibly a "comma" for a total of 30 characters. Using the number 30, I have several different ways in which I can take "30" and create different sized matrices (6x5, 2x15, 1x30, 3x10).

Take the 6x5 matrix for example -- here's how you can identify a character based on which element of the matrix is "filled-in."

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Space Period Question Comma

So, to identify the letter "R" the matrix would look like the following:

And, using the schema in the first matrix, the name "Scott" would look like this:


                        O S T T

Or you could reverse it if you have a picture that is heavily black (instead of white -- the black-and-white extract below is definitely weighted towards the white end of the scale).


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                        O S T T

Needless to say, the same approach...