Systems and methods for developing and verifying image processing standards for mobile deposit

• US 8,983,170 B2
• Filed: 03/15/2013
• Issued: 03/17/2015
• Est. Priority Date: 01/18/2008
• Status: Active Grant

• Current Assignee: Mitek Systems Incorporated
• Original Assignee: Mitek Systems Incorporated
• Inventors: Nepomniachtchi, Grigori, Strange, Mike
• Primary Examiner(s): MOTSINGER, SEAN T
• Application Number:
  US13/844,533
• Publication Number:
  US 20130223721A1
• Time in Patent Office: 732 Days
• Field of Search: None
• US Class Current: 382/137
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06V 10/24 Aligning, centring, orientation detection or correction of the image
• CPC Class Codes: G06V 10/993 Evaluation of the quality of the acquired pattern
• CPC Class Codes: G06V 30/133 Evaluation of quality of the acquired characters
• CPC Class Codes: G06V 30/2253 Recognition of characters printed with magnetic ink G06V30/2247 takes precedence
• CPC Class Codes: G06V 30/414 Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text
• CPC Class Codes: G06V 30/418 Document matching, e.g. of document images

Abstract

Systems and methods are provided for assessing whether mobile deposit processing engines meet specified standards for mobile deposit of financial documents. A mobile deposit processing engine (MDE) is evaluated to determine if it can perform technical capabilities for improving the quality of and extracting content from an image of a financial document. A verification process then begins, where the MDE performs the image quality enhancements and text extraction steps on sets of images from a test deck. The results of the processing of the test deck are then evaluated by comparing confidence levels with thresholds to determine if each set of images should be accepted or rejected. Further analysis determines whether any of the sets of images were falsely accepted or rejected in error. An overall error rate is then compared with minimum accuracy criteria, and if the criteria are met, the MDE meets the standard for mobile deposit.

Claims

1. A method for verifying image processing standards for mobile deposit of a financial document, comprising:

receiving sets of test images of financial documents captured by a mobile device;

performing an image processing transaction on each set of test images to improve the image quality of at least one aspect of each set of test images and extract at least one category of text from each set of test images;

determining a confidence level for each category of extracted text;

comparing the confidence level of each category of extracted text with a corresponding threshold value to accept or reject the image processing transaction for each set of test images;

comparing the at least one category of extracted text with known values of the at least one category of extracted text for each set of test images to determine whether the acceptance or rejection of the image processing transaction for each set of test images was in error;

calculating an error rate of acceptances or rejections of the image processing transaction based on a number of determined errors from the image processing transactions for the sets of test images; and

comparing the error rate with one or more accuracy criteria and verifying an accuracy of the mobile deposit processing unit if the error rate is within the one or more accuracy criteria, or rejecting the accuracy of the mobile deposit processing unit if the error rate falls outside of the one or more accuracy criteria.

2. The method of claim 1, wherein each set of test images include a first image of a front side of a check and a second image of a back side of the check.

3. The method of claim 1, wherein a statistically significant portion of the sets of test images are good quality images and a statistically significant portion of the sets of test images are poor quality images.

4. The method of claim 1, wherein improving the image quality of at least one aspect of each set of test images includes correcting a geometric distortion, cropping and binarizing each set of test images.

5. The method of claim 1, wherein the categories of extracted text include at least one of:

MICR line, payment amount and endorsement signature.

6. The method of claim 5, wherein the image processing transaction is accepted if the MICR line and the payment amount were correctly read.

7. The method of claim 6, wherein the image processing transaction is accepted if the image quality meets a defined image quality threshold.

8. The method of claim 1, wherein the accuracy criteria includes a maximum threshold of:

false image quality acceptances, false image quality rejections, false MICR line acceptances, false payment amount acceptances, false payment amount rejections, false image quality rejections and incorrect image quality rejections.

9. The method of claim 8, wherein the accuracy of the mobile deposit processing unit is verified only if all of the accuracy criteria are met.

18. The system of claim 8, wherein the accuracy of the mobile deposit processing unit is verified only if all of the accuracy criteria are met.

10. A system for verifying image processing standards for mobile deposit of a financial document, comprising:

a receiving unit which receives sets of test images of financial documents captured by a mobile device;

a mobile deposit processing unit which performs an image processing transaction on each set of test images to improve the image quality of at least one aspect of each set of test images and extract at least one category of text from each set of test images;

an evaluation unit which determines a confidence level for each category of extracted text;

a threshold unit which compares the confidence level of each category of extracted text with a corresponding threshold value to accept or reject the image processing transaction for each set of test images;

an error determination unit which compares the at least one category of extracted text with known values of the at least one category of extracted text for each set of test images to determine whether the acceptance or rejection of the image processing transaction for each set of test images was in error;

an error rate calculation unit which calculates an error rate of acceptances or rejections of the image processing transaction based on a number of determined errors from the image processing transactions for the sets of test images; and

a verification unit which compares the error rate with one or more accuracy criteria and verifies an accuracy of the mobile deposit processing unit if the error rate is within the one or more accuracy criteria or rejects the accuracy of the mobile deposit processing unit if the error rate falls outside of the one or more accuracy criteria.

11. The system of claim 10, wherein each set of test images include a first image of a front side of a check and a second image of a back side of the check.

12. The system of claim 10, wherein a statistically significant portion of the sets of test images are good quality images and a statistically significant portion of the sets of test images are poor quality images.

13. The system of claim 10, wherein improving the image quality of at least one aspect of each set of test images includes correcting a geometric distortion, cropping and binarizing each set of test images.

14. The system of claim 10, wherein the categories of extracted text include at least one of:

MICR line, payment amount and endorsement signature.

15. The system of claim 14, wherein the image processing transaction is accepted if the MICR line and the payment amount were correctly read.

16. The system of claim 15, wherein the image processing transaction is accepted if the image quality meets a defined image quality threshold.

17. The system of claim 10, wherein the accuracy criteria includes a maximum threshold of:

false image quality acceptances, false image quality rejections, false MICR line acceptances, false payment amount acceptances, false payment amount rejections, false image quality rejections and incorrect image quality rejections.