Personal information retrieval using knowledge bases for optical character recognition correction

• US 20070133874A1
• Filed: 12/12/2005
• Published: 06/14/2007
• Est. Priority Date: 12/12/2005
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Bressan, Marco, Dejean, Herve, Dance, Christopher
• Granted Patent: US 7,826,665 B2
• Time in Patent Office: Days
• US Class Current: 382/181
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/12 Detection or correction of errors, e.g. by rescanning the pattern
• CPC Class Codes: G06V 30/268 Lexical context

Abstract

In a system for updating a contacts database (42, 46), a portable imager (12) acquires a digital business card image (10). An image segmenter (16) extracts text image segments from the digital business card image. An optical character recognizer (OCR) (26) generates one or more textual content candidates for each text image segment. A scoring processor (36) scores each textual content candidate based on results of database queries respective to the textual content candidates. A content selector (38) selects a textual content candidate for each text image segment based at least on the assigned scores. An interface (50) is configured to update the contacts list based on the selected textual content candidates.

Claims

1. A system for updating a contacts database, the system comprising:

a portable imager configured to acquire a digital business card image;

an image segmenter configured to extract text image segments from the digital business card image;

an optical character recognizer (OCR) configured to generate one or more textual content candidates for each text image segment;

a scoring processor configured to score textual content candidates based on results of database queries respective to the textual content candidates;

a content selector that selects a textual content candidate for each text image segment based at least on the assigned scores; and

an interface configured to update the contacts database based on the selected textual content candidates.

2. The system as set forth in claim 1, wherein the portable imager includes a cellular telephone including a built-in camera.

3. The system as set forth in claim 1, wherein the portable imager includes a handheld document scanner.

4. The system as set forth in claim 1, wherein the scoring processor comprises:

a local scoring processor component configured to compute a score for each textual content candidate based on results of database queries respective to that textual content candidate; and

a global scores adjustment component configured to selectively adjust scores of textual content candidates based on results of database queries respective to other textual content candidates.

5. The system as set forth in claim 1, further comprising:

a computer embodying at least the OCR and scoring processor, the computer being physically distinct from the portable imager.

6. The system as set forth in claim 1, wherein at least the image segmenter, OCR, and scoring processor reside on the portable imager.

7. The system as set forth in claim 1, wherein the interface comprises:

a user interface configured to allow an associated user to accept or edit the selected textual content candidates prior to updating the contacts database.

8. A method for acquiring personal information, the method comprising:

acquiring a business card image;

extracting a text image segment from the business card image;

applying optical character recognition (OCR) to the text image segment to generate a plurality of textual content candidates;

querying at least one database respective to each of the textual content candidates; and

selecting a most likely one of the textual content candidates based at least on records returned by the querying.

9. The method as set forth in claim 8, further comprising:

extracting a second text image segment from the business card image;

applying OCR to the second text image segment to generate a plurality of second text image textual content candidates;

querying the at least one database respective to each of the second text image textual content candidates; and

selecting a most likely one of the second text image textual content candidates based on records returned by the querying.

10. The method as set forth in claim 9, wherein the selecting of a most likely one of the textual candidates is further based on records returned by the querying of the at least one database respective to the second text image textual content candidates.

11. The method as set forth in claim 8, wherein the selecting comprises:

assigning a score to each textual content candidate based at least on the returned records; and

selecting the most likely one of the textual content candidates based on the assigned scores.

12. The method as set forth in claim 11, wherein the assigning of scores comprises:

weighting the scores based on a reliability weighting of at least one database from which at least one record is returned.

13. The method as set forth in claim 8, wherein the acquiring of the business card image comprises:

photographing the business card using a built-in camera of a cellular telephone.

14. The method as set forth in claim 8, further comprising:

extracting a logo image segment from the business card image; and

querying at least one image database respective to the logo image segment, the selecting of a most likely one of the textual candidates being further based on records returned by the querying of the at least one image database respective to the logo image segment.

15. A system for generating a textual contact record from textual content candidates extracted by optical character recognition (OCR) from text image segments of a business card image, the system comprising:

a databases query that queries at least one database respective to the textual content candidates and collects records returned responsive to the queries;

a content candidates scoring processor that assigns scores to the textual content candidates based on the collected records; and

a content selector that selects a textual content candidate for each text image segment based at least on the assigned scores.

16. The system as set forth in claim 15, wherein the content candidates scoring processor comprises:

a local scoring processor that assigns a score to each textual content candidate based on records returned by queries respective to the textual content candidate.

17. The system as set forth in claim 16, wherein the content candidates scoring processor further comprises:

a global adjuster that modifies the score of a first textual content candidate that was extracted by OCR from a corresponding first text image segment when at least one record returned by a query respective to a second textual content candidate that was extracted by OCR from a second text image segment also includes the first textual content candidate.

18. The system as set forth in claim 16, wherein the system is further provided with at least one logo image segment extracted from the business card image, and the system further comprises:

an image databases query that image queries at least one image database respective to the logo image segment and collects textual metadata returned responsive to the image query; and

a global adjuster that modifies the score of a selected textual content candidate when the collected textual metadata includes the selected textual content candidate.

19. The system as set forth in claim 15, wherein the at least one database queried by the database query includes a plurality of databases, and the content candidates scoring processor further comprises:

stored database weights corresponding to the databases, the scores assigned based on the collected records incorporating the database weights of the databases from which the records were collected.

20. The system as set forth in claim 19, wherein the content candidates scoring processor further comprises:

a database weights adjuster that adjusts the stored database weights based on ongoing accuracy of support for textual content candidates provided by the databases.

21. The system as set forth in claim 15, wherein the content candidates scoring processor further comprises:

a tagging adjuster that selectively adjusts tags assigned to the text image segments of the business card image based on the collected records.

22. The system as set forth in claim 15, wherein the content candidates scoring processor assigns a score to the textual content candidates extracted from a first text image segment based on (i) records collected responsive to queries respective to textual content candidates of the first text image segment and (ii) records collected responsive to queries respective to textual content candidates of text image segments other than the first text image segment.

23. The system as set forth in claim 15, wherein each textual content candidate has a confidence level assigned thereto by the OCR, and the content selector selects the textual content candidate for each text image segment based on the OCR-assigned confidence levels adjusted by the assigned scores.