Method and system for identifying anchors for fields using optical character recognition data

• US 9,396,540 B1
• Filed: 04/03/2013
• Issued: 07/19/2016
• Est. Priority Date: 03/28/2012
• Status: Active Grant

• Current Assignee: Open Text Corporation
• Original Assignee: EMC Corporation (Dell Technologies Inc.)
• Inventors: Sampson, Steven
• Primary Examiner(s): Nguyen, Phong
• Application Number:
  US13/855,933
• Time in Patent Office: 1,203 Days
• Field of Search: 707/737, 707/749, 707/758
• US Class Current: 1/1
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/50 of still image data
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 30/196 using sequential comparisons of the image signals with a plurality of references
• 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

Identifying anchors for fields using optical character recognition data is described. A collection of characters is identified. The collection of characters includes a first set of characters at a first position relative to a first field in a first document and a second set of characters at a second position relative to the first field in the first document. The first set of characters is associated with a first word, and the second set of characters is associated with a second word. An anchor is created based on the collection of characters, wherein the anchor is at a third relative position to the first field in the first document. A second field is identified in a second document by identifying the anchor in the second document.

Claims

1. A system for identifying anchors for fields using optical character recognition data, the system comprising:

one or more processors; and

a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to;

identify a first collection of characters comprising a first set of characters at a first position relative to a first field in a first document and a second set of characters at a second position relative to the first field in the first document, wherein the first set of characters is associated with a first word and the second set of characters is associated with a second word;

create a first anchor in the first document based on the first collection of characters, wherein the first anchor is at a third position relative to the first field in the first document, and wherein the first anchor is associated with a second field in the first document;

identify a second collection of characters comprising a third set of characters at a fourth position relative to a third field in a second document and a fourth set of characters at a fifth position relative to the third field in the second document, wherein the third set of characters is associated with a third word and the fourth set of characters is associated with a fourth word;

determine a location of a second anchor in the second document by calculating a vector based on the first, second, third and fourth sets of characters; and

identify a fourth field in the second document that corresponds to the second field in the first document based on the location of the second anchor in the second document.

2. The system of claim 1, wherein at least one of the first set of characters comprise a first word and the second set of characters comprise a second word.

3. The system of claim 1, wherein at least one of the first document and the second document comprise digitized optical character recognition data.

4. The system of claim 1, wherein the second document is associated with a class in response to a comparison to classify documents similar to the first document.

5. The system of claim 1, wherein the second document is associated with a template in response to a comparison to classify documents similar to the first document.

6. The system of claim 1, wherein the instructions to determine the location of the second anchor in the second document based on the calculated vector comprises instructions to generate a score based on a degree of similarity between the second anchor in the second document and the first anchor in the first document, and comparing the score to a threshold.

7. The system of claim 1, wherein the instructions to create the first anchor further comprises instructions to combine a graphic with the first set of characters and the second set of characters to create the first anchor.

8. A computer-implemented method for identifying anchors for fields using optical character recognition data, the method comprising:

identifying a first collection of characters comprising a first set of characters at a first position relative to a first field in a first document and a second set of characters at a second position relative to the first field in the first document, wherein the first set of characters is associated with a first word and the second set of characters is associated with a second word;

combining the first set of characters with the second set of characters to create a first anchor in the first document based on the first collection of characters, wherein the first anchor is at a third position relative to the first field in the first document, and wherein the first anchor is associated with a second field in the first document;

identifying a second collection of characters comprising a third set of characters at a fourth position relative to a third field in a second document and a fourth set of characters at a fifth position relative to the third field in the second document, wherein the third set of characters is associated with a third word and the fourth set of characters is associated with a fourth word;

determining a location of a second anchor in the second document by calculating a vector based on the first, second, third and fourth sets of characters; and

identifying a fourth field in the second document that corresponds to the second field in the first document based on the location of the second anchor in the second document.

9. The computer-implemented method of claim 8, wherein at least one of the first set of characters comprise a first word and the second set of characters comprise a second word.

10. The computer-implemented method of claim 8, wherein at least one of the first document and the second document comprise digitized optical character recognition data.

11. The computer-implemented method of claim 8, wherein the second document is associated with a class in response to a comparison to classify documents similar to the first document.

12. The computer-implemented method of claim 8, wherein the second document is associated with a template in response to a comparison to classify documents similar to the first document.

13. The computer-implemented method of claim 8, wherein determining the location of the second anchor in the second document based on the calculated vector comprises generating a score based on a degree of similarity between the second anchor in the second document and the first anchor in the first document, and comparing the score to a threshold.

14. The computer-implemented method of claim 8, wherein creating the first anchor further comprises combining a graphic with the first set of characters and the second set of characters to create the first anchor.

15. A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein, the computer-readable program code adapted to be executed by one or more processors to implement a method for identifying anchors for fields using optical character recognition data, the method comprising:

identifying a first collection of characters comprising a first set of characters at a first position relative to a first field in a first document and a second set of characters at a second position relative to the first field in the first document, wherein the first set of characters is associated with a first word and the second set of characters is associated with a second word;

combining the first set of characters with the second set of characters to create a first anchor in the first document based on the first collection of characters, wherein the first anchor is at a third position relative to the first field in the first document, and wherein the first anchor is associated with a second field in the first document;

identifying a second collection of characters comprising a third set of characters at a fourth position relative to a third field in a second document and a fourth set of characters at a fifth position relative to the third field in the second document, wherein the third set of characters is associated with a third word and the fourth set of characters is associated with a fourth word;

determining a location of a second anchor in the second document by calculating a vector based on the first, second, third and fourth sets of characters; and

identifying a fourth field in the second document that corresponds to the second field in the first document based on the location of the second anchor in the second document.

16. The computer program product of claim 15, wherein at least one of the first set of characters comprise a first word and the second set of characters comprise a second word.

17. The computer program product of claim 15, wherein at least one of the first document and the second document comprise digitized optical character recognition data.

18. The computer program product of claim 15, wherein the second document is associated with a class in response to a comparison to classify documents similar to the first document.

19. The computer program product of claim 15, wherein the second document is associated with a template in response to a comparison to classify documents similar to the first document.

20. The computer program product of claim 15, wherein determining the location of the second anchor in the second document based on the calculated vector comprises generating a score based on a degree of similarity between the second anchor in the second document and the first anchor in the first document, and comparing the score to a threshold.