Mobile Check Deposit OCR Flow With Delayed Image Upload
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Solution Overview
Problem
Conventional remote check deposit systems face challenges in capturing clear and precise images of checks, particularly on resource-constrained devices, leading to user frustration and inefficiencies in optical character recognition (OCR) processes.
Innovation Solution
A method and system for remote check deposit using a mobile device that performs optical character recognition (OCR) locally, verifies image quality, and provides user-controlled image capture, with optional hybrid processing on both the mobile device and server, enhancing privacy, security, and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If OCR is performed on a server for remote check deposit, then processing power and accuracy are improved, but network bandwidth consumption and data exposure increase
Solution Approach 1:
The patent extracts the OCR processing function from the server environment and implements it locally on the mobile device. This extraction eliminates the need to transmit check images to the server for OCR processing, thereby reducing network bandwidth consumption and data exposure while maintaining OCR functionality.
Solution Approach 2:
The patent introduces an intermediary OCR engine that runs locally on the mobile device, acting as a mediator between the check image capture and the deposit submission process. This local OCR engine processes images on-device without requiring server-side processing, reducing network dependency.
2Loss of energy
If OCR is performed on a mobile device, then network bandwidth is reduced and privacy is improved, but processing speed and accuracy may deteriorate
Solution Approach 1:
The mobile device performs self-service by executing OCR processing locally without requiring external server assistance. The device independently captures check images, processes them through the local OCR engine, and submits only the extracted data, making the system self-sufficient and reducing network dependency.
3Ease of operation
If automatic image capture is implemented, then user convenience is improved, but image quality control and user frustration reduce
Solution Approach 1:
The system implements feedback by analyzing captured images through local OCR processing and providing information about image quality and data extraction success. This feedback loop allows the system to identify problematic captures and prompt users to retake images, improving overall image quality while maintaining ease of operation.
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.