Systems and methods for classifying payment documents during mobile image processing

• US 10,607,073 B2
• Filed: 09/23/2019
• Issued: 03/31/2020
• Est. Priority Date: 01/18/2008
• Status: Active Grant

• Current Assignee: Mitek Systems Incorporated
• Original Assignee: Mitek Systems Incorporated
• Inventors: Nepomniachtchi, Grigori, Kliatskine, Vitali, Kotovich, Nikolay
• Primary Examiner(s): Motsinger, Sean T
• Application Number:
  US16/579,625
• Publication Number:
  US 20200019770A1
• Time in Patent Office: 190 Days
• CPC Class Codes: G06Q 20/042 characterized in that the payment protocol involves at least one cheque
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/1448 based on markings or identifiers characterising the document or the area
• CPC Class Codes: G06V 30/2253 Recognition of characters printed with magnetic ink G06V30/2247 takes precedence
• CPC Class Codes: G06V 30/40 Document-oriented image-based pattern recognition
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables
• CPC Class Codes: G06V 30/418 Document matching, e.g. of document images

Abstract

Systems and methods are provided for processing an image of a financial payment document captured using a mobile device and classifying the type of payment document in order to extract the content therein. These methods may be implemented on a mobile device or a central server, and can be used to identify content on the payment document and determine whether the payment document is ready to be processed by a business or financial institution. The system can identify the type of payment document by identifying features on the payment document and performing a series of steps to determine probabilities that the payment document belongs to a specific document type. The identification steps are arranged starting with the fastest step in order to attempt to quickly determine the payment document type without requiring lengthy, extensive analysis.

Claims

1. A system comprising:

a feature knowledge database configured to store a plurality of document models generated from feature information for a plurality of document types, wherein the document model comprises probabilistic indications associated with each feature, wherein the probabilistic indications indicate the likelihood that a document is a certain type of document; and

one or processors configured to execute instructions, the one or processors communicatively coupled with the feature knowledge database, the instructions configured to cause the processor to;

receive an image of a new document,

extract feature information for a plurality of features from the image;

compare the feature information to the feature information included in the plurality of document models, wherein the features are compared one at a time,

for each feature being compared, assess a probability that the new document is a certain document type of the plurality of document types based on the probabilistic indications for the given feature and prior features that have been extracted and compared; and

when the probability that the new document is the certain document type exceeds a threshold, then determine that the new document is that certain document type.

2. The system of claim 1, wherein the system is implemented on a mobile device.

3. The system of claim 1, wherein the document types are related to types of checks.

4. The system of claim 3, wherein the feature information is related to at least some of the MICR line, codeline one or more barcodes, check number, and lock icon.

5. The system of claim 3, wherein the feature information is related to geometric features.

6. The system of claim 5, wherein the geometric features include at least some of width, height, and aspect ratio.

7. The system of claim 5, wherein the instructions are further configured to cause the one or more processors to use the geometric features to eliminate certain document models of the plurality of document models.

8. The system of claim 4, wherein the instructions are further configured to cause the one or more processors to first identify the presence of the lock icon and the location, and to identify the corresponding document type based thereon.

9. The system of claim 8, wherein the instructions are further configured to cause the one or more processors to then determine the presence and type-specific properties of the MICR line, if present, and to identify the corresponding document type based thereon.

10. The system of claim 1, wherein the instructions are further configured to cause the one or more processors to determine that the new document is fraudulent based on the probabilistic indications for the given feature and prior features that have been extracted and compared.