IP Library Granted Patent US 12705914
Granted Patent B2
US 12705914 · App. 18/244,318 · Granted Aug 11, 2026

Intelligent and mode-based optical character recognition

Inventor: Rohit Pradeep Shetty (Bangalore, IN)
Assignee: Omnissa, LLC
G06V30/1801G06V30/19113
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Quick Facts
Patent No.
US 12705914
App. No.
18/244,318
Granted
Aug 11, 2026
Kind
B2
Abstract

Disclosed are various embodiments for intelligent text recognition based upon a selected pattern detection mode. First, text can be identified in an image. A pattern detection mode can be selected by a user or autonomously. In some instances, the pattern detection mode can be selected based at least in part on a user account. Next, the text can be parsed for occurrences of a pattern associated with the selected pattern detection mode. A list of occurrences of the pattern can be generated from the text and presented to a user. In some instances, a user can train a model to learn a new pattern.

Claims (53)

1 . A system, comprising:

a computing device comprising a processor and a memory; and

machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least:

process an image comprising text by using an optical character recognition (OCR) engine to identify the text in the image and generate machine-encoded text based on the identified text;

select, from a plurality of pattern detection modes, a pattern detection mode associated with a pattern defining a format for a plurality of consecutive characters, wherein selecting the pattern detection mode is based on one or more context factors associated with a user account, wherein the one or more context factors include a user interaction history, a mode selection history, or a client device location associated with the user account;

parse the machine-encoded text to identify one or more occurrences of the pattern associated with the selected pattern detection mode;

generate an occurrence list comprising the one or more occurrences of the pattern identified in the machine-encoded text; and

cause a client device associated with the user account to display the occurrence list in a user interface with an option to select the one or more occurrences from the occurrence list.

2 . The system of claim 1 , wherein the machine-readable instructions further cause the computing device to at least:

obtain a request to generate a new pattern;

generate a test pattern based at least in part on training data;

identify one or more occurrences of the test pattern within the text;

save the one or more occurrences of the test pattern in a test list;

generate a prompt for a score on the test list;

obtain a score based at least in part on the test list; and

create the new pattern based at least in part on the test pattern and the score.

3 . The system of claim 1 , wherein the pattern detection mode is customized based at least in part on the user account.

4 . The system of claim 1 , wherein the plurality of pattern detection modes comprise at least one of: an email address mode, a date mode, or a phone number mode.

5 . The system of claim 1 , wherein the selected pattern detection mode is selected by obtaining, from a user interface, a selection of a pattern detection mode.

6 . A method, comprising:

processing, by a computing device, an image comprising text by using an optical character recognition (OCR) to identify the text in the image and generate machine-encoded text based on the identified text;

selecting, by the computing device from a plurality of pattern detection modes, a pattern detection mode associated with a pattern defining a format for a plurality of consecutive characters, wherein selecting the pattern detection mode is based on one or more context factors associated with a user account, wherein the one or more context factors include a user interaction history, a mode selection history, or a client device location associated with the user account;

parsing, by the computing device, the machine-encoded text to identify one or more occurrences of the pattern associated with the selected pattern detection mode;

generating, by the computing device, an occurrence list comprising the one or more occurrences of the pattern identified in the machine-encoded text; and

causing a client device associated with the user account to display the occurrence list in a user interface with an option to select the one or more occurrences from the occurrence list.

7 . The method of claim 6 , further comprising:

obtaining, by the computing device, a request to generate a new pattern;

generating, by the computing device, a test pattern based at least in part on training data;

identifying, by the computing device, one or more occurrences of the test pattern within the text;

saving, by the computing device, the one or more occurrences of the test pattern in a test list;

generating, by the computing device, a prompt for a score on the test list;

obtaining, by the computing device, a score based at least in part on the test list; and

creating, by the computing device, the new pattern based at least in part on the test pattern and the score.

8 . The method of claim 6 , wherein the pattern detection mode is customized based at least in part on the user account.

9 . The method of claim 6 , wherein the plurality of pattern detection modes include at least one of: an email address mode, a date mode, or a phone number mode.

10 . The method of claim 6 , wherein the selected pattern detection mode is selected by obtaining, from a user interface, a selection of a pattern detection mode.

11 . A non-transitory, computer-readable medium, comprising machine readable instructions that, when executed by a processor of a computing device, cause the computing device to at least:

process an image comprising text by using an optical character recognition (OCR) engine to identify the text in the image and generate machine-encoded text based on the identified text;

select, from a plurality of pattern detection modes, a pattern detection mode associated with a pattern defining a format for a plurality of consecutive characters, wherein selecting the pattern detection mode is based on one or more context factors associated with a user account, wherein the one or more context factors include a user interaction history, a mode selection history, or a client device location associated with the user account;

parse the machine-encoded text to identify one or more occurrences of the pattern associated with the selected pattern detection mode;

generate an occurrence list comprising the one or more occurrences of the pattern identified in the machine-encoded text; and

cause a client device associated with the user account to display the occurrence list in a user interface with an option to select the one or more occurrences from the occurrence list.

12 . The non-transitory, computer-readable medium of claim 11 , wherein the machine-readable instructions further cause the computing device to at least:

obtain a request to generate a new pattern;

generate a test pattern based at least in part on training data;

identify one or more occurrences of the test pattern within the text;

save the one or more occurrences of the test pattern in a test list;

generate a prompt for a score on the test list;

obtain a score based at least in part on the test list; and

create a new pattern based at least in part on the test pattern and the score.

13 . The non-transitory, computer-readable medium of claim 11 , wherein the pattern detection mode is customized based at least in part on the user account.

14 . The non-transitory, computer-readable medium of claim 11 , wherein the plurality of pattern detection modes include at least one of: an email address mode, a date mode, or a phone number mode.

15 . The non-transitory, computer-readable medium of claim 11 , wherein the selected pattern detection mode is selected by obtaining, from a user interface, a selection of a pattern detection mode.