IP Library › Granted Patent US 12682327
Granted Patent B2
US 12682327 · App. 19/399,992 · Granted Jul 14, 2026

Mobile check deposit

Inventors: Marlen L. Foster (Fairfield, CA); Connie K. Yung (San Francisco, CA); Vijay Narayanan (San Jose, CA); Raj M. Bharadwaj (Plymouth, MN); Soumitri Naga Kolavennu (Plymouth, MN); Jessica G. Winberg (Prescott, WI); Balasubramanian Narayanan (Minneapolis, MN); Hima Rama Subrahmanyam Vishnubhotla (Suwanee, GA); Jayalakshmi Mangalagiri (Lakeville, MN); Ali Marjani (Cary, NC); Teja Dade (Omaha, NE); Michael Starace (Oakland, CA); David Robinson (Burnsville, MN)
Assignee: U.S. Bank National Association
G06Q20/0425G06Q20/108G06Q20/3223G06Q20/326G06Q20/4016G06Q20/42G06Q40/02G06V30/19013G06V30/19093G06V30/1916G06V30/2253
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Quick Facts
Patent No.
US 12682327
App. No.
19/399,992
Granted
Jul 14, 2026
Kind
B2
Abstract

Methods and systems for remote check deposit are disclosed. A check for deposit is processed without the need for a server to receive any image of the check initially. Instead, optical character recognition (OCR) data is received at the server from a mobile device. Verification processing for the check is then performed using the OCR data. If the verification process is successful, a confirmation notification is sent to the mobile device. Subsequently, after sending the confirmation notification, a check image is received, from which the OCR data was determined. The check is, in turn, processed for deposit using the received check image.

Claims (108)

1 . A method comprising:

receiving an image having a region of interest;

performing a binary conversion on the image to produce a binarized image;

generating contours for the region of interest in the binarized image;

applying a convex hull operation to the generated contours for the binarized image;

obtaining a set of corners from the generated contours following the application of the convex hull operation;

evaluating the set of corners;

determining that the set of corners passes the evaluation;

evaluating a quality of the image;

determining that the image passes the evaluation of quality; and

providing the image for further processing after determining that the set of corners passes the evaluation and that the image passes the evaluation of quality.

2 . The method of claim 1 , wherein evaluating the set of corners includes performing at least one operation from the corner evaluation group consisting of:

evaluating absolute size defined by the corners;

evaluating relative size defined by the corners;

evaluating whether a region of interest is in frame based on the corners;

evaluating corner angles of the corners;

validating consistency based on the corners; and

validating an aspect ratio based on the corners.

3 . The method of claim 2 , wherein evaluating the set of corners includes performing at least three operations from the corner evaluation group.

4 . The method of claim 2 , wherein evaluating the set of corners includes performing at least five operations from the corner evaluation group.

5 . The method of claim 2 ,

wherein evaluating absolute size defined by the corners includes deriving a height from at least two of the corners and a length from at least two of the corners and comparing the height and length to respective thresholds;

wherein evaluating relative size defined by the corners includes calculating an area of the image bounded by the contours relative the overall size of the image;

wherein evaluating whether a region of interest is in frame based on the corners includes determining whether the corners lie within a threshold distance away from an edge of the image;

wherein evaluating corner angles of the corners includes determining whether angles of the corners fall within a predetermined acceptable range;

wherein validating consistency based on the corners includes:

determining that a left height of a left side and a right height of a right side are within a certain threshold amount or percentage of each other; and

determining that a top length of a top side and a bottom length of a bottom side are within a certain threshold amount or percentage of each other; and

wherein validating an aspect ratio based on the corners includes deriving a height from at least two of the corners and a length from at least two of the corners and comparing a ratio based on the height and length to an acceptable ratio.

6 . The method of claim 1 , wherein evaluating the quality of the image includes performing at least one operation from a quality evaluation group consisting of:

a noise detection operation;

a minimal background validation operation;

a brightness validation operation;

a contrast validation operation;

a text contrast validation operation;

an image focus validation operation; and

a glare detection operation.

7 . The method of claim 6 , wherein evaluating the quality includes performing at least three operations from the quality evaluation group.

8 . The method of claim 6 , wherein evaluating the quality includes performing at least five operations from the quality evaluation group.

9 . The method of claim 6 ,

wherein the noise detection operation includes:

comparing the image to a blurred version of the image to form a comparison;

measuring a variance of pixel intensities based on the comparison; and

flagging the image as noisy responsive to the variance being below a predetermined threshold;

wherein the minimal background validation operation includes:

detecting a main rectangle in the image;

determining a ratio of the area of the main rectangle to an overall area of the image; and

flagging the image responsive to the ratio exceeding a threshold;

wherein the brightness validation operation includes:

creating a grayscale version of the image;

determining an average brightness of the grayscale version;

flagging the image responsive to the average brightness not falling within an acceptable brightness range;

wherein the contrast validation operation includes:

creating a grayscale version of the image;

determining an average contrast of the grayscale version;

flagging the image responsive to the average contrast not falling within an acceptable contrast range;

wherein the text contrast validation operation includes:

calculating a text region average pixel intensity of a text region in the image;

calculating a non-text region average pixel intensity of a non-text region in the image;

flagging the image if a ratio between the text region pixel intensity and the non-text region average pixel intensity does not satisfy a threshold;

wherein the image focus validation operation includes:

applying a filter to a grayscale version of the image;

measuring a variance based on the filtered grayscale version; and

flagging the image responsive to the variance failing to satisfy a threshold; and

wherein the glare detection operation includes:

calculating an area of regions having significant brightness in a grayscale version of the image;

comparing the area of regions having significant brightness with a total image area of the image to form a ratio; and

flagging the image responsive to the ratio exceeding or failing to satisfy a threshold.

10 . The method of claim 1 , further comprising:

performing one or more image conversion or cleanup steps with respect to the image.

11 . The method of claim 1 , further comprising:

applying one or more morphological modifications to the binarized image selected from the group consisting of: light erosion, heavy erosion, inversion with light erosion, and inversion with heavy erosion.

12 . The method of claim 1 , further comprising:

applying a correction selected from the group consisting of: a position normalizing operation; a proportion normalizing operation; a skewing operation; a deskewing operation; a rotation operation; a scaling operation; a stretching operation; and a moving operation.

13 . The method of claim 1 , wherein determining that the image passes the evaluation of quality includes determining that the evaluation of quality did not flag the image.

14 . The method of claim 1 , wherein providing the image for further processing includes applying an optical character recognition technique to the image.

15 . The method of claim 1 , wherein the method is performed by one or more processors of a mobile device having a camera.

16 . The method of claim 1 , wherein the region of interest is a check within the image.

17 . The method of claim 16 ,

wherein generating the contours for the region of interest includes incorrectly generating a convexity within the check; and

wherein applying the convex hull operation results in correcting the convexity.

18 . The method of claim 1 , further comprising:

capturing the image using a camera of a device; and

wherein the device performs the method.

19 . A set of one or more non-transitory computer-readable media having instructions thereon that when executed by a set of one or more processors, cause the set of one or more processors to:

receive an image having a region of interest;

perform a binary conversion on the image to produce a binarized image;

generate contours for the region of interest in the binarized image;

apply a convex hull operation to the generated contours for the binarized image;

obtain a set of corners from the generated contours following the application of the convex hull operation;

evaluate the set of corners;

determine that the set of corners passes the evaluation;

evaluate a quality of the image;

determine that the image passes the evaluation of quality; and

provide the image for further processing after determining that the set of corners passes the evaluation and that the image passes the evaluation of quality.

20 . An apparatus comprising:

a set of one or more processors; and

a set of one or more non-transitory computer-readable media having instructions thereon that when executed by the set of one or more processors, cause the set of one or more processors to:

receive an image having a region of interest;

perform a binary conversion on the image to produce a binarized image;

generate contours for the region of interest in the binarized image;

apply a convex hull operation to the generated contours for the binarized image;

obtain a set of corners from the generated contours following the application of the convex hull operation;

evaluate the set of corners;

determine that the set of corners passes the evaluation;

evaluate a quality of the image;

determine that the image passes the evaluation of quality; and

provide the image for further processing after determining that the set of corners passes the evaluation and that the image passes the evaluation of quality.