Mobile Device Real-Time Image Quality Evaluation for Remote Deposit
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Solution Overview
Problem
Existing remote deposit systems require image quality evaluation at a backend system, leading to inefficiencies and additional resource consumption, as well as potential duplicate presentment or fraud issues.
Innovation Solution
The technology enables real-time or near real-time multiple-image OCR processing on mobile or desktop devices, allowing for continuous evaluation of image quality and extraction of check data fields without transmitting images to a remote system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image quality evaluation is performed at a backend remote system, then centralized control and security are improved, but system resource consumption and processing time increase
Solution Approach 1:
The patent divides the image quality evaluation function into two segments: a preliminary evaluation performed locally on the mobile device, and a comprehensive evaluation performed at the backend system. This segmentation allows the system to quickly filter out obviously poor quality images locally, reducing the time and resources required for backend processing while maintaining centralized control for final approval.
Solution Approach 2:
The patent implements preliminary image quality evaluation on the mobile device before transmitting images to the backend system. This preliminary action filters out unusable images early in the process, preventing waste of backend system resources and reducing overall processing time while maintaining centralized control for final image approval.
2Measurement precision
If multiple images are transmitted to a remote system for evaluation, then image quality assessment accuracy is improved, but network resource consumption and processing overhead increase
Solution Approach 1:
The patent applies partial action by performing a preliminary image quality evaluation on the mobile device that assesses the most critical quality parameters. This partial evaluation filters out clearly unacceptable images before full multi-image transmission to the backend, reducing network resource consumption while maintaining sufficient assessment accuracy for preliminary filtering.
Solution Approach 2:
The patent implements local quality assessment on the mobile device that evaluates image quality parameters specific to the user's capture conditions. This local evaluation is optimized for the specific device and lighting conditions, providing accurate enough assessment for preliminary filtering without requiring complete backend analysis of all images.
3Manufacturing precision
If image recapture is required due to quality issues, then image quality standards are maintained, but user experience and operational efficiency deteriorate
Solution Approach 1:
The patent performs preliminary image quality evaluation on the mobile device immediately after capture, providing users with instant feedback on whether their images meet quality standards. This preliminary action allows users to correct issues like lighting or focus before submission, maintaining quality standards while improving user experience by providing immediate guidance rather than delayed rejection.
Solution Approach 2:
The patent implements a feedback mechanism where the mobile device provides users with quality assessment results and specific guidance for improvement. This feedback loop enables users to understand what needs to be corrected and how to fix it, maintaining image quality standards while making the process more user-friendly and reducing the need for complete recapture.
4Loss of information
If all captured images are transmitted to the backend system, then complete data availability is improved, but system resource usage and processing time increase
Solution Approach 1:
The patent performs preliminary image quality evaluation and filtering on the mobile device before transmission to the backend system. This preliminary action ensures that only images with sufficient quality meet the basic criteria for submission, maintaining data availability for valid images while significantly reducing the volume of data that requires backend processing and improving overall system efficiency.
Data Source
AI summary
A computer implemented method, system and non-transitory computer-readable device for a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a live stream of image data of a field of view of at least one camera, wherein the live stream includes imagery of at least a portion of the financial instrument. The method continues by extracting in real-time, based on the formation of byte array objects from the live stream of image data, data fields from a ranked sequence of imagery to be processed by an optical character recognition (OCR) program resident on the client device. The OCR process extracts one or more data fields from of the financial instrument that are communicated to a remote deposit server to complete the electronic deposit.