Image processing and identification system, method and apparatus

• US 20060059116A1
• Filed: 08/19/2005
• Published: 03/16/2006
• Est. Priority Date: 08/20/2004
• Status: Active Grant

• Current Assignee: XWEB Incorporated
• Original Assignee: XWEB Incorporated
• Inventors: Levi, Ronald M., Shprung, Shai
• Granted Patent: US 7,555,487 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

Embodiments of the present invention are directed to a system and method for processing and identifying a first data file, the first data file having set of data points, wherein each data point is defined by an x,y coordinate and has a value corresponding to the lightness or darkness of the data resident at the data point, comprising: dividing the first data file into segments; identifying the coordinates of at least one contrast point for each segment; creating a first set of identifiers for the data file, creating a second set of identifiers for a second data file, comparing at least one identifier of the first data file to the corresponding identifier in the second data file; and assessing whether at least a portion of the second data file matches at least a portion of the first data file.

Claims

1. A method for processing and identifying a first data file, the first data file having a set of data points, wherein each data point is defined by an x,y coordinate and has a value corresponding to the brightness of the data resident at the data point, comprising:

dividing the first data file into segments;

identifying the coordinates of at least one contrast data point for each segment;

creating a first set of identifiers for the first data file, wherein at least one of the identifiers is derived from the data contained in the first data file, and wherein at least one identifier is associated with at least one segment;

identifying a second data file, wherein the content of the second data file is unknown;

creating a second set of identifiers for the second data file, each identifier in the second set of identifiers corresponding to an identifier in the first set of identifiers, wherein at least one of the second set identifiers is derived from the data contained in the second data file, and wherein at least one of the second set identifiers is associated with at least one segment;

comparing at least one identifier of the first data file to the corresponding identifier in the second set of identifiers; and

assessing whether at least a portion of the second data file matches at least a portion of the first data file.

2. A method as claimed in claim 1, further comprising:

dividing the second data file into segments;

identifying the coordinates of at least one contrast data point for each segment for the second data file.

3. A method as claimed in claim 1, wherein assessing whether a portion of the second data files matches a portion of the first data file, comprises:

calculating the difference of the values of at least one identifier in the first set of identifiers and the corresponding identifier in the second set of identifiers, wherein the selected identifier is associated with a particular segment; and

assigning a scoring value for the segment based upon the difference between the values of the identifier from the first set of identifiers and the identifier from the second set of identifiers.

4. A method as claimed in claim 1, wherein creating a first set of identifiers comprises:

selecting a subset of segments for the first data file;

calculating the difference between the value of the red pixels in the subset of segments and the value of blue pixels in the subset of segments; and

summing the value of the data coordinates identifying the contrast point for each segment in the data file.

5. A method as claimed in claim 1, wherein creating a first set of identifiers comprises:

summing the values of each x coordinate for each identified contrast point and storing the value in a database; and

summing the values of each y coordinate for each identified contrast point and storing the value in a database.

6. A method as claimed in claim 1, wherein creating a first set of identifiers comprises:

selecting a subset of segments for the first data file; and

calculating the difference of the values of the red pixels and blue pixels for the second subset of segments.

7. A method as claimed in claim 1, further comprising:

calculating a brightness value for the first data file, wherein the brightness value is the difference between the total number of bright pixels and the total number of dark pixels for a selected subset of segments;

calculating a brightness value for the second data file, wherein the brightness value is the difference between the total number of bright pixels and the total number of dark pixels for the selected subset of segments; and

comparing the brightness value of the first data file and the brightness value of the second data file.

8. A method as claimed in claim 7, further comprising:

visually reviewing the second data file if the brightness value for the first data file substantially matches the brightness value for the second data file; and

eliminating the second data file as a false positive if the difference between the brightness value for the first data file and the brightness value for the second data file exceeds a predefined tolerance.

9. A method as claimed in claim 8, further comprising:

transmitting notification that the second file is an unauthorized use of the first data file, if the brightness values are within the predefined tolerance.

10. A method as claimed in claim 1, wherein identifying the contrast point further comprises:

selecting a segment from the group of segments;

selecting the first data point as the currently identified contrast point and storing the value of the first data point;

comparing the value of the currently identified contrast point to the value of each data point in the segment until the value of one of the data points in the segment differs from the value of the currently identified contrast point by a predefined amount, identifying the data point having a value differing from the value of the currently identified contrast point as the new currently identified contrast point; and

repeating comparing the value of the currently identified contrast point to each remaining data point in the segment until the currently identified contrast point is replaced with a newly identified contrast point, or until all of the remaining data points in the segment have been compared.

12. A method as claimed in claim 1, wherein the first data and second data file have an original orientation, further comprising comparing the original orientation of the first data file and the second data file.

13. A method as claimed in claim 10, wherein the value of the data point is calculated by summing the values of the selected data point and data points proximally located to the selected data point and dividing the summation by a predefined integer, wherein the integer is less than the number of data points used in the summation.

14. A method for identifying whether at least a portion of an unknown data file is a copy of a known data file, the known data file having set of data points, wherein each data point has a value corresponding to the lightness or darkness of the data resident at the data point, comprising:

dividing the known data file into segments;

identifying at least one contrast point for each segment, wherein the contrast point identifies at least one point having a value, wherein the absolute difference between the value of the contrast point and the value of each point in the segment, exceeds a predefined amount;

creating a first set of identifiers for the known data file, wherein at least one of the identifiers is derived from the data contained in the data file;

assessing the likelihood of a match between the known data file and the unknown data file.

15. A method as claimed in claim 14, further comprising:

selecting a first subset of segments for the first data file;

calculating the difference between the value of the red pixels in the subset of segments and the value of blue pixels in the subset of segments; and

summing the value of the data coordinates identifying the contrast point for each segment;

identifying whether a segment is important; and

assigning a scoring value to each segment, wherein the scoring value is associated with whether the segment is identified as important.

16. A method as claimed in claim 14, further comprising:

identifying at least one second data file, wherein the content of the second data file is unknown;

dividing the second data file into segments;

identifying the coordinates of at least one contrast data point for each segment for the second data file;

selecting a subset of segments for the second data file;

calculating the difference of the values of the red pixels and blue pixels for the subset of segments for the second data file;

summing the values of each x coordinate for each identified contrast point and storing the value in a database;

summing the values of each y coordinate for each identified contrast point and storing the value in a database; and

comparing at least one identifier for a segment in the second data file with the corresponding identifier for the first data file; and

assigning a scoring value for the segment based upon the difference between the values of the identifier from the identifier for the second data file and the identifier from the second data file.