Candidate identification by image fingerprinting and model matching

• US 8,977,054 B2
• Filed: 08/06/2014
• Issued: 03/10/2015
• Est. Priority Date: 08/29/2011
• Status: Active Grant

• Current Assignee: DST Technologies, Inc. (SS&C Technologies Holdings Incorporated)
• Original Assignee: DST Technologies, Inc. (SS&C Technologies Holdings Incorporated)
• Inventors: Highley, Joshua O.
• Primary Examiner(s): DRENNAN, BARRY T
• Application Number:
  US14/452,701
• Publication Number:
  US 20140355890A1
• Time in Patent Office: 216 Days
• Field of Search: None
• US Class Current: 382/177
• CPC Class Codes: G06V 10/242 by image rotation, e.g. by 90 degrees
• CPC Class Codes: G06V 10/754 involving a deformation of the sample pattern or of the reference pattern; Elastic matching
• CPC Class Codes: G06V 10/768 using context analysis, e.g. recognition aided by known co-occurring patterns
• CPC Class Codes: G06V 30/2264 using word shape
• CPC Class Codes: G06V 30/412 Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables
• CPC Class Codes: G06V 30/414 Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text
• CPC Class Codes: G06V 30/418 Document matching, e.g. of document images

Abstract

Candidate identification utilizing fingerprint identification is disclosed. The method includes receiving a candidate image comprising a plurality of constituent elements arranged in a content pattern, compensating for rotation variation in the content pattern of the received candidate, analyzing each of the plurality of constituent elements comprising the content pattern of the received candidate image to define a bounded area about each of the plurality of constituent elements, building a candidate fingerprint representative of the content pattern wherein the candidate fingerprint is based on the defined bounded area, comparing the candidate fingerprint to a plurality of fingerprints wherein each of the plurality of fingerprints represents one of a plurality of exemplars, identifying one of the plurality of fingerprints that corresponds to the candidate fingerprint, and evaluating the candidate and one or more identified exemplars to determine the best match there between, wherein the identified exemplar corresponds to the one of the plurality of fingerprints.

Claims

1. A method of candidate identification utilizing fingerprint identification, the method comprising:

receiving a candidate comprising a plurality of pixels arranged on a background;

identifying at least two subsets of the plurality of pixels where each pixel in a subset is within a threshold distance of at least one other pixel in the subset and wherein each pixel within one subset is not within the threshold distance of any pixel of any other of the at least two subsets;

determining one representative pixel for each of the identified at least two subsets;

building a candidate fingerprint of the candidate based on the determined representative pixels and not on the remaining pixels of each of the at least two subsets;

comparing the candidate fingerprint to a plurality of exemplar fingerprints, each corresponding to one of a plurality of exemplars and determining the best match there between; and

identifying the candidate based on the exemplar corresponding to the exemplar fingerprint which best matches the candidate fingerprint.

2. The method of claim 1, wherein the plurality of pixels are arranged on the background to form a plurality of constituent content elements of a content pattern and further wherein the constituent content elements of the content pattern include elements selected from the group consisting of:

character components;

word components and text line components.

3. The method of claim 2, further comprising compensating for rotation variation identified in the content pattern of the received candidate by applying a Hough transformation to the plurality of constituent elements.

4. The method of claim 1, wherein the candidate comprises an electronic document image.

5. The method of claim 4, wherein the candidate further comprises a content pattern comprising at least one of handwritten information, imaging skew, or image noise.

6. The method of claim 4 further comprising:

determining more than one of the plurality of exemplar fingerprints which best match the candidate fingerprint.

7. The method of claim 1 further comprising:

designating the candidate as an unknown if it does not correspond to one of a plurality of exemplars.

8. The method of claim 1, wherein each of the at least two subsets comprises a bounded area comprising the subset of the plurality of pixels thereof, and wherein each of the pixels within one of the bounded areas represents a pixel within the threshold distance of another of the remaining pixels within that bounded area.

9. The method of claim 1, wherein the fingerprint comprises at least one list of coordinates corresponding to the determined representative pixels.

10. The method of claim 9, wherein the at least one list includes a first list corresponding to characters represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels;

a second list corresponding to words represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels and a third list corresponding to text lines represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels.

11. The method of claim 1 wherein the threshold distance comprises a vertical threshold distance and a horizontal threshold distance.

12. The method of claim 11 wherein at least one of the vertical threshold distance or horizontal threshold distance may be iteratively varied.

13. The method of claim 1 wherein the threshold distance defines an amount of white space between pixels to separately group into subsets the pixels representative of at least one of a character, a word or a text line.

14. The method of claim 1 wherein, for each of the identified at least two subsets, the determined representative pixel thereof is one of the subset.

15. The method of claim 1 wherein each of the plurality of exemplar fingerprints is associated with a context, the method further comprising ascribing the context associated with the exemplar which best matches the candidate fingerprint to the candidate fingerprint.

16. The method of claim 1 wherein the identifying further comprises ignoring a subset of the plurality of pixels when the number of pixels therein is below a first threshold, when the vertical width of the pixels therein as arranged on the candidate is less than a second threshold, or the horizontal width of the pixels therein as arranged on the candidate is less than a third threshold, or a combination thereof.

17. The method of claim 1 wherein the arrangement of the plurality pixels of the candidate comprises private sensitive information, the candidate fingerprint being free thereof such that the candidate fingerprint may be communicated over a non-secure network.

18. A system for candidate identification utilizing a fingerprint, the system comprising:

a processor coupled with a memory having computer readable instructions stored therein and operable to cause the processor to;

receive a candidate comprising a plurality of pixels arranged on a background;

identify at least two subsets of the plurality of pixels where each pixel in a subset is within a threshold distance of at least one other pixel in the subset and wherein each pixel within one subset is not within the threshold distance of any pixel of any other of the at least two subsets;

determine one representative pixel for each of the identified at least two subsets;

build a candidate fingerprint of the candidate based on the determined representative pixels and not on the remaining pixels of each of the at least two subsets;

compare the candidate fingerprint to a plurality of exemplar fingerprints, each corresponding to one of a plurality of exemplars and determining the best match there between; and

identify the candidate based on the exemplar corresponding to the exemplar fingerprint which best matches the candidate fingerprint.

19. The system of claim 18, wherein the plurality of pixels are arranged on the background to form a plurality of constituent content elements of a content pattern and further wherein the constituent content elements of the content pattern include elements selected from the group consisting of:

character components;

word components and text line components.

20. The system of claim 19, wherein the computer readable instructions are further operable to cause the processor to compensate for rotation variation identified in the content pattern of the received candidate by applying a Hough transformation to the plurality of constituent elements.

21. The system of claim 18, wherein the candidate comprises an electronic document image.

22. The system of claim 21, wherein the candidate further comprises a content pattern comprising at least one of handwritten information, imaging skew, or image noise.

23. The system of claim 21, wherein the computer readable instructions are further operable to cause the processor to determine more than one of the plurality of exemplar fingerprints which best match the candidate fingerprint.

24. The system of claim 18, further wherein the computer readable instructions are further operable to cause the processor to designate the candidate as an unknown if it does not correspond to one of a plurality of exemplars.

25. The system of claim 18, wherein each of the at least two subsets comprises a bounded area comprising the subset of the plurality of pixels thereof, and wherein each of the pixels within one of the bounded areas represents a pixel within the threshold distance of another of the remaining pixels within that bounded area.

26. The system of claim 18, wherein the fingerprint comprises at least one list of coordinates corresponding to the determined representative pixels.

27. The system of claim 26, wherein the at least one list includes a first list corresponding to characters represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels;

a second list corresponding to words represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels and a third list corresponding to text lines represented by the at least two subsets of the plurality of pixels represented by each of the determined representative pixels.

28. The system of claim 18, wherein the threshold distance comprises a vertical threshold distance and a horizontal threshold distance.

29. The system of claim 28, wherein at least one of the vertical threshold distance or horizontal threshold distance may be iteratively varied.

30. The system of claim 18, wherein the threshold distance defines an amount of white space between pixels to separately group into subsets the pixels representative of at least one of a character, a word or a text line.

31. The system of claim 18, wherein, for each of the identified at least two subsets, the determined representative pixel thereof is one of the subset.

32. The system of claim 18, wherein each of the plurality of exemplar fingerprints is associated with a context, the method further comprising ascribing the context associated with the exemplar fingerprint which best matches the candidate fingerprint to the candidate fingerprint.

33. The system of claim 18, wherein the computer readable instructions are further operable to cause the processor to ignore a subset of the plurality of pixels when the number of pixels therein is below a first threshold, when the vertical width of the pixels therein as arranged on the candidate is less than a second threshold, or the horizontal width of the pixels therein as arranged on the candidate is less than a third threshold, or a combination thereof.

34. The system of claim 18, wherein the arrangement of the plurality pixels of the candidate comprises private sensitive information, the candidate fingerprint being free thereof such that the candidate fingerprint may be communicated over a non-secure network.

35. A method of candidate identification utilizing fingerprint identification, the method comprising:

receiving a candidate comprising a plurality of pixels arranged on a background;

identifying at least two subsets of the plurality of pixels where each pixel in a subset is within a threshold distance of at least one other pixel in the subset and wherein each pixel within one subset is not within the threshold distance of any pixel of any other of the at least two subsets;

determining one representative pixel for each of the identified at least two subsets;

building a candidate fingerprint of the candidate based on the determined representative pixels and not on the remaining pixels of each of the at least two subsets;

communicating the candidate fingerprint over a network;

receiving the candidate fingerprint;

comparing the candidate fingerprint to a plurality of exemplar fingerprints, each corresponding to one of a plurality of exemplars and determining the best match there between, wherein each of the plurality of exemplar fingerprints is associated with a context based on the corresponding exemplar;

identifying the candidate based on the exemplar corresponding to the exemplar fingerprint which best matches the candidate fingerprint; and

ascribing the context associated with the exemplar fingerprint, which best matches the candidate fingerprint, to the candidate fingerprint.