IP Library Granted Patent US 10,303,937
Granted Patent B2
US 10,303,937 · App. 15/888,484 · Granted May 28, 2019

Systems and methods for mobile image capture and content processing of driver's licenses

Inventors: Grigori Nepomniachtchi (San Diego, CA); Mike Strange (San Diego, CA)
Assignee: MITEK SYSTEMS, INC.
G06K9/00442G06K9/3275G06K9/38G06K9/42G06Q20/3276G07C9/00H04N1/00708H04N1/00718H04N1/00734G06K2209/01G07C2209/41H04N1/00244H04N1/00307H04N2101/00H04N2201/001H04N2201/0084
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Quick Facts
Patent No.
US 10,303,937
App. No.
15/888,484
Granted
May 28, 2019
Kind
B2
Abstract

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Claims (25)

1. A computer-implemented method of processing an image, comprising:

receiving an image captured by a camera included in a mobile device;

performing a shape detection test on the image to produce a first set of coordinates representing a set of edges of the image;

performing an internal feature detection test on the image to produce a second set of coordinates associated with a feature set of the image, wherein the internal feature detection test, comprises:

identifying a photo are within the image,

determining an aspect ratio of the photo, and

determining the type of document associate with the image based at least in part on the aspect ratio;

combining the first set of coordinates and the second set of coordinates to generate a set of adjustment parameters associated with the image;

adjusting the image based at least on the adjustment parameters;

outputting the adjusted image.

2. The computer-implemented method of claim 1 , wherein prior to performing the internal feature detection test on the document image, the method further comprises pre-filtering the document image using a low-pass noise suppression filter.

3. The computer-implemented method of claim 1 , wherein the adjustment parameters includes both coordinates associated with the feature set of the document image and coordinates representing the set of edges of the document image.

4. The computer-implemented method of claim 1 , wherein the feature detection test detects a set of feature points in the document image by detecting a set of local maxima in the document image.

5. The computer-implemented method of claim 4 , wherein the internal feature detection test constructs the feature set by computing local gradients and color distributions in the areas of the set of feature points.

6. The computer-implemented method of claim 1 , wherein the shape detection test includes a rectangular shape detection test.

7. The computer-implemented method of claim 1 , wherein prior to combining the first set of coordinates and the second set of coordinates to generate the adjustment parameters, a rounded corner detection test on the document image to produce a third set of coordinates associated with the feature set of the document image.

8. The computer-implemented method of claim 7 , wherein generating the set of adjustment parameters further includes combining the first set of coordinates and the second set of coordinates with the third set of coordinates.

9. The computer-implemented method of claim 1 , wherein performing the internal feature detection test on the document image includes:

detecting a set of feature points in the document image;

constructing a set of feature descriptors based on the set of feature points;

wherein the feature matching operation between the set of feature descriptors and a set of predetermined features of the document template.

10. The computer-implemented method of claim 9 , wherein detecting the set of feature points in the document image includes detecting a set of local maxima in the document image.

11. The computer-implemented method of claim 9 , wherein constructing the set of feature descriptors based on the set of feature points includes computing local gradients and color distributions in the areas of the set of feature points.

12. The computer-implemented method of claim 1 , wherein the outputs of the feature matching operation include a transformation matrix containing a set of matched feature points.

13. The computer-implemented method of claim 1 , further comprising binarizing the adjusted image to produce a binarized adjusted image.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 5, 2018
From: NEPOMNIACHTCHI, GRIGORI; STRANGE, MIKE
To: MITEK SYSTEMS, INC.
Reel/Frame 045248/0717 →
Continuity (8)
Continuation 15652126 · Jul 17, 2017
Continuation 15083177 · Mar 28, 2016
Continuation 13844476 · Mar 15, 2013
Continuation In Part 12906036 · Oct 15, 2010
Continuation In Part 12778943 · May 12, 2010
Continuation In Part 12346026 · Dec 30, 2008
Provisional Application 61022279 · Jan 18, 2008
Related Publication 20180232572A1 · Aug 16, 2018
Cited By (10)
US 12,229,734 US 12,265,952 US 12,346,884 US 12,381,989 US 12,406,311 US 12,499,422 US 12,499,423 US 12,682,327 US 12,699,970 US 12,705,587