Mobile Check Deposit OCR Validation With Delayed Image Upload
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Solution Overview
Problem
Traditional remote check deposit processes face challenges in capturing clear and precise images of checks, particularly on resource-constrained devices, leading to user frustration and inefficiencies, and existing optical character recognition (OCR) methods struggle to accurately extract data from checks with varying fonts, especially the MICR line.
Innovation Solution
A mobile device-based system performs local optical character recognition (OCR) on check images, verifies image quality and data completeness, and provides user-controlled image capture, followed by server validation, ensuring accurate data extraction and secure transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional remote check deposit processes are used, then users can deposit checks remotely, but image quality and data extraction accuracy deteriorate due to resource constraints on mobile devices
Solution Approach 1:
The system segments the OCR processing into two parts: initial extraction performed on the mobile device and validation/refinement performed on the server. This segmentation allows the mobile device to handle only the essential extraction task while the server handles the computationally intensive validation, resolving the contradiction between extraction accuracy and device resource constraints.
Solution Approach 2:
The server acts as an intermediary between the mobile device and the final deposit confirmation. The mobile device sends extracted data to the server for validation against the original check image, allowing accurate data extraction without requiring the mobile device to have sufficient resources for comprehensive validation processing.
2Measurement precision
If comprehensive OCR validation is performed on the server, then data extraction accuracy improves, but network bandwidth consumption and server load increase
Solution Approach 1:
The system performs partial validation on the server rather than complete re-processing. The server validates the extracted data against the original check image but does not perform full OCR processing, achieving sufficient validation accuracy while minimizing network bandwidth consumption and server computational load.
3Measurement precision
If users manually review captured check images, then image quality improves, but processing time and user effort increase
Solution Approach 1:
The system provides automated feedback to users about the quality of captured check images by analyzing the extracted OCR data. If the extracted data is complete and accurate, the system confirms successful capture without requiring manual review, thereby maintaining image quality while minimizing processing time and user effort.
Data Source
AI summary
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.