AI-Driven Document Image Transformation for Distorted Inputs

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Solution Overview

Problem

Existing document image transformation technologies are inflexible and sensitive to unexpected inputs, such as rotated, incomplete, or distorted documents, and are limited to specific document types, requiring high resource costs and manual intervention.

Innovation Solution

A document image transformation tool that utilizes AI/ML models to generate template definitions, perform noise reduction, align images with templates, and produce digestible data through noise elimination and conversion, enabling the processing of multiple document types.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional document digestion technology is used, then processing speed for standard documents is maintained, but the system fails to handle unexpected inputs such as rotated, incomplete, or distorted documents

Engineering Contradiction:

Improveability to handle unexpected document inputsVSAvoidprocessing reliability for varied document types

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system dynamically adjusts processing parameters and applies different transformation operations based on the detected state of the document image. When rotation, distortion, or incomplete views are detected, the system automatically adapts its behavior to handle these variations, rather than failing with fixed processing pipelines

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system performs preliminary analysis of the document image to detect its state (rotation, distortion, completeness) before main processing begins. This preliminary action allows the system to prepare appropriate processing parameters and select suitable transformation operations in advance, ensuring reliable handling of varied inputs

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If bespoke document digestion systems are created for specific document types, then processing accuracy for that document type is optimized, but resource costs increase and versatility decreases

Engineering Contradiction:

Improveprocessing accuracyVSAvoidsystem complexity and resource requirements

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system implements a universal document digestion framework that can handle multiple document types through a single unified processing pipeline. By using general-purpose transformation operations and adaptive parameters, the system achieves multi-functionality without requiring separate bespoke systems for each document type, thereby reducing overall complexity and resource costs

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system achieves high accuracy for different document types by dynamically changing processing parameters rather than using fixed specialized systems. When a new document type is encountered, the system adjusts parameters such as transformation thresholds, extraction criteria, and validation rules to optimize processing for that specific type while maintaining the same underlying framework

Inventive Principle:

Principle #35Parameter changes

3Productivity

If conventional document processing is used, then simple documents can be processed quickly, but manual intervention is required for unexpected inputs increasing operational complexity

Engineering Contradiction:

Improveprocessing throughputVSAvoiduser-friendliness and automation level

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system performs self-diagnosis and self-correction by automatically detecting document states and applying appropriate transformations without requiring user intervention. When unexpected inputs are detected, the system autonomously adjusts processing parameters and applies corrective transformations, eliminating the need for manual intervention and maintaining high productivity across varied inputs

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250272481A1Method and system for transforming structured documents into digestible input data

Publication Date: 2025.08.28 JPMORGAN CHASE BANK NA

AI summary

A system is provided for implementing a document image transformation tool that transforms an image of at least one physical document into digestible data. The system stores instructions that cause a processor to: generate a first template definition of a first type of document; transform, based on the template definition, the image of the at least one physical document into a transformed image of the at least one physical document; produce, based on the template definition, input data from the transformed image of the at least one physical document; compute, based on the transforming and the producing, analytics that identify at least one parameter of a result of the transforming and the producing; associate, via an association, the input data with the analytics; and digest at least one from among the input data, the analytics, and the association.