Text extraction using optical character recognition

Patent metadata

Field	Value
Publication number	US-2024212375-A1
Application number	US-202418599667-A
Country	US
Kind code	A1
Filing date	Mar 8, 2024
Priority date	May 10, 2022
Publication date	Jun 27, 2024
Grant date	—

Abstract

Provided herein are systems and methods for extracting text from a document. Different optical character recognition (OCR) tools are used to extract different versions of the text in the document. Metrics evaluating the quality of the extracted text are compared to identify and select higher quality extracted text. A selected portion of text is compared to a threshold to ensure minimal quality. The selected portion of text is then saved. Error correction can be applied to the selected portion of text based on errors specific to the OCR tools or the document contents.

First claim

What is claimed is:

1 . A method, comprising:
extracting, by at least one processor, a first set of text from a document using a first optical character recognition (OCR) tool; extracting, by the at least one processor, a second set of text from the document using a second OCR tool; comparing, by the at least one processor, a first metric of the first set of text to a second metric of the second set of text, the first metric measuring a first level of OCR quality of the first set of text and the second metric measuring a second level of OCR quality of the second set of text; selecting, by the at least one processor, a first selected text from the first set of text or the second set of text based on a higher level of OCR quality; extracting, by the at least one processor, a third set of text from the document using a third OCR tool; comparing, by the at least one processor, a corresponding metric of the first selected text to a third metric of the third set of text, the third metric measuring a third level of OCR quality of the third set of text; selecting, by the at least one processor, a second selected text from the first selected text or the third set of text based on a higher level of OCR quality; and storing, by the at least one processor, the second selected text as a final text in a searchable format.

2 . The method of claim 1 , wherein the extracting any of the first set of text, the second set of text, or the third set of text from the document comprises:
converting, by the at least one processor, the document into a set of images, each page of the document being converted into a respective image from the set of images; and extracting, by the at least one processor, any of the first set of text, the second set of text, or the third set of text from at least one of the respective images from the set of images.

3 . The method of claim 1 , further comprising:
identifying, by the at least one processor, a group of characters in a selected potion of any of the first set of text, the second set of text, or the third set of text comprising an erroneous character, wherein the erroneous character is expected to be a different character based on the group of characters; and correcting, by the at least one processor, the selected portion of text by changing the erroneous character to the different character.

4 . The method of claim 1 , further comprising:
identifying, by the at least one processor, two or more characters in a selected portion of any of the first set of text, the second set of text, or the third set of text that is missing a space between two characters in the two or more characters; and correcting, by the at least one processor, the selected portion of text by adding the space between the two characters in the two or more characters.

5 . The method of claim 1 , further comprising:
identifying, by the at least one processor, a superscript character or a subscript character in a group of characters in a selected portion of any of the first set of text, the second set of text, or the third set of text that is unexpected based on the group of characters; and correcting, by the at least one processor, the selected portion of text by deleting the superscript character or the subscript character from the group of characters.

6 . The method of claim 1 , wherein the first metric, the second metric and the third metric comprise a respective number of words in the first set of text, the second set of text and the third set of text extracted from the document.

7 . The method of claim 1 , further comprising:
determining, for the first set of text, the second set of text, and the third set of text, a fourth metric, wherein the fourth metric is a respective number of words in respective ones of the first set, second set or third set of extracted texts from the document divided by a number of pages in the document.

8 . A system, comprising:
one or more processors; memory communicatively coupled to the one or more processors, the memory storing instructions which, when executed by the one or more processors, cause the one or more processors to: extract a first set of text from a document using a first optical character recognition (OCR) tool; extract a second set of text from the document using a second OCR tool; compare a first metric of the first set of text to a second metric of the second set of text, the first metric measuring a first level of OCR quality of the first set of text and the second metric measuring a second level of OCR quality of the second set of text; select, based on the comparing, a first selected text from the first set of text or the second set of text based on a higher level of OCR quality; extract a third set of text from the document using a third OCR tool; compare a corresponding metric of the first selected text to a third metric of the third set of text, the third metric measuring a third level of OCR quality of the third set of text; select a second selected text from the first selected text or the third set of text based on a higher level of OCR quality; and store the second selected text as a final text in a searchable format.

9 . The system of claim 8 , wherein the instructions further cause the one or more processors to:
extract any of the first set of text, the second set of text, or the third set of text from the document by: converting the document into a set of images, each page of the document being converted into a respective image from the set of images; and extracting any of the first set of text, the second set of text, or the third set of text from at least one of the respective images from the set of images.

10 . The system of claim 8 , wherein the instructions further cause the one or more processors to:
identify a group of characters in a selected potion of any of the first set of text, the second set of text, or the third set of text comprising an erroneous character, wherein the erroneous character is expected to be a different character based on the group of characters; correct, by the at least one processor, the selected portion of text by changing the erroneous character to the different character.

11 . The system of claim 8 , wherein the instructions further cause the one or more processors to:
identify two or more characters in a selected portion of any of the first set of text, the second set of text, or the third set of text that is missing a space between two characters in the two or more characters based on the two or more characters; and correct the selected portion of text by adding the space between the two characters in the two or more characters.

12 . The system of claim 8 , wherein the instructions further cause the one or more processors to:
identify a superscript character or a subscript character in a group of characters in a selected portion of any of the first set of text, the second set of text, or the third set of text that is unexpected based on the group of characters; and correct the selected portion of text by deleting the superscript character or the subscript character from the group of characters.

13 . The system of claim 8 , wherein the first metric, the second metric and the third metric comprise a respective number of words in the first set of text, the second set of text and the third set of text extracted from the document.

14 . The system of claim 8 , wherein the instructions further cause the one or more processors to:
determine, for the first set of text, the second set of text, and the third set of text, a fourth metric, wherein the fourth metric is a respective number of

Assignees

• Capital One Services Llc

Inventors

• Demchalk Chris
• Parker Ryan M
• Kumar Lokesh Vijay
• Fromknecht Brian

Classifications

• G06V30/26

  Techniques for post-processing, e.g. correcting the recognition result · CPC title

• G06V30/41

  Analysis of document content (recognition of printed characters based on code marks G06V30/224) · CPC title

• G06V30/155

  Removing patterns interfering with the pattern to be recognised, such as ruled lines or underlines · CPC title

• G06V30/133 Primary

  Evaluation of quality of the acquired characters · CPC title