Image Scan Synchronization for Check Processing
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Solution Overview
Problem
Financial institutions face challenges in diagnosing and resolving chronic image quality issues that lead to rejected check images due to varying image quality standards among banks, which results in significant time and cost inefficiencies, especially when commercially available image quality assessment tools do not disclose proprietary algorithms.
Innovation Solution
A system and method for synchronizing image scan settings between banks, involving multiple scans with different settings, feedback analysis, and statistical methods to determine optimal scan settings that align with unknown recipient bank standards, reducing non-conforming images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple scans with different settings are performed to determine optimal scan settings, then image quality conformity is improved, but processing time increases
Solution Approach 1:
The system performs preliminary scans with different settings to determine optimal scan settings before actual check processing. This preliminary action establishes a static combination of settings that can then be applied consistently, reducing the need for repeated trial scans while maintaining high conformity rates.
Solution Approach 2:
The system varies scan parameters (such as brightness, contrast, resolution) across multiple test scans to identify which parameter combinations produce images that meet recipient bank standards. By systematically changing parameters and analyzing results, the system determines the optimal setting combination for subsequent processing.
2Manufacturing precision
If scan settings are adjusted for each individual check to handle variability, then image quality is improved, but operational complexity increases
Solution Approach 1:
The system applies different scan settings based on the specific characteristics of each check type or population. Rather than using a single universal setting or complex individual adjustment for every check, the system identifies local optimal settings for different check categories (e.g., different paper types, ink types, check formats) and applies those settings accordingly.
Solution Approach 2:
The system dynamically determines optimal scan settings through an iterative process involving multiple scans and feedback analysis. The settings are adjusted based on performance data and recipient bank feedback, allowing the system to adapt to varying check conditions while maintaining automated operation without requiring manual adjustment for each individual check.
3Productivity
If a static combination of scan settings is used to simplify processing, then processing speed is improved, but image quality conformity decreases
Solution Approach 1:
The system performs preliminary scanning and analysis to determine the optimal static combination of settings before high-speed processing begins. This preliminary action captures the essential characteristics of the check population and establishes settings that will maintain conformity during subsequent high-speed operation.
Solution Approach 2:
The system identifies and applies the critical parameter values that have the greatest impact on image quality conformity. By focusing on the most significant parameters and setting them optimally, the system achieves high conformity rates with a static configuration, avoiding the need for continuous adjustment during high-speed processing.
4Loss of information
If proprietary image assessment algorithms are analyzed to understand recipient bank standards, then image quality standards understanding is improved, but information accessibility decreases
Solution Approach 1:
The system uses feedback from recipient banks regarding rejected images to infer their assessment criteria. By analyzing which images are rejected and why, the system reverse-engineers the recipient bank's quality standards and adjusts its scanning and filtering algorithms accordingly, even without direct access to proprietary assessment software.
Solution Approach 2:
The system creates a model or representation of the recipient bank's quality standards based on observed rejection patterns and feedback. This copied understanding of standards allows the sending bank to pre-screen images and adjust scanning parameters to match recipient expectations, effectively replicating the assessment criteria without needing access to the actual proprietary algorithms.
Data Source
AI summary
A tool may be provided that may allow a first party (e.g., a sending bank) to synchronize its image scan settings with unknown image assessment standards of a second party (e.g., a recipient bank). However, such a tool may be used within a single party that performs both scanning and image assessment, and is not limited for use between two or more parties.