Form Data Extraction via User-Defined Field Location
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Solution Overview
Problem
Existing form processing programs require significant customization work to extract data from scanned images and transfer it to target applications, involving tedious and expensive setup processes due to the need for prior knowledge of form layouts and specific integration with target applications.
Innovation Solution
A method and system that allows data extraction from scanned images by prompting users to indicate field locations, creating templates automatically, and using these templates to match and extract data from similar layouts without the need for initial customization, enabling automatic data transfer to target applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If form processing programs use OCR techniques to extract data from scanned images, then data capture efficiency is improved, but significant customization work is required for each form layout
Solution Approach 1:
The system performs self-learning by automatically analyzing form images and identifying field locations and data patterns without requiring manual customization. The software learns from the form structures it processes and adapts its extraction rules automatically, eliminating the need for users to manually configure templates for each form layout.
Solution Approach 2:
The system dynamically adjusts its processing parameters and extraction rules based on the detected form layout characteristics. By changing parameters such as field location thresholds, data patterns, and matching criteria adaptively, the system maintains high extraction accuracy across diverse form formats without requiring manual reconfiguration.
2Measurement precision
If form processing programs require prior knowledge of form layouts, then data extraction accuracy is improved, but the setup process becomes tedious and expensive
Solution Approach 1:
The system performs preliminary learning and analysis during the initial processing of form images, automatically building knowledge about form layouts, field locations, and data patterns. This preliminary action occurs automatically in the background without requiring manual setup, allowing the system to achieve high extraction accuracy on subsequent forms of the same type.
Solution Approach 2:
The software automatically learns and adapts to different form layouts by analyzing the structural characteristics of processed forms. It self-configures extraction rules, identifies field boundaries, and learns data patterns without human intervention, thereby achieving accurate extraction while eliminating tedious setup processes.
3Adaptability or versatility
If form processing programs integrate with specific target applications, then data transfer functionality is improved, but integration work requires significant customization
Solution Approach 1:
The system employs a universal data transfer interface that can adapt to multiple target applications through standardized data formats and protocols. By implementing multi-functional capability to work with various applications (accounting software, CRM systems, databases) through a common interface, the system provides broad adaptability without requiring application-specific customization for each integration scenario.
4Ease of manufacture
If commercial off-the-shelf form processing products are used, then initial customization costs are reduced, but the products may not meet specific business requirements
Solution Approach 1:
The system transitions from static, pre-configured processing rules to dynamic, adaptive rules that automatically adjust based on the specific form types and business requirements encountered. This dynamic capability allows the software to start as a general-purpose solution and then adapt to specific business needs through automated learning, combining the advantages of both off-the-shelf products and customized solutions.
Data Source
AI summary
A form processing method for extracting data items from a form previously digitized in the form of a digital image, the method comprising prompting a user to indicate a location of one or more physical fields each physical field relating to a data item of specific type; receiving one or more indications provided by the user on the location of the physical fields; and identifying content and location of the data items of the physical fields using related data formats.