IBDM Server Table Generator for Form Data
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Solution Overview
Problem
Existing systems for converting form images into symbolic information are error-prone, particularly for handwritten data, requiring expensive human intervention and consuming computing resources, making it inefficient for aggregating and querying purposes.
Innovation Solution
A system and method utilizing an Image Based Document Management (IBDM) server that generates tables from form images by identifying label and field images, sorting them based on metadata, and allowing user interaction for modification, which includes a query engine to process requests and update the table dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If symbolic conversion is performed on form images using OCR or OMR, then information can be aggregated and processed, but the conversion is error-prone and requires expensive human intervention
Solution Approach 1:
The patent introduces an image-based document management system as an intermediary between form images and symbolic data processing. Instead of directly converting images to symbolic information using error-prone OCR/OMR, the system creates a structured image-based representation that preserves visual information while enabling efficient querying and aggregation, thus maintaining accuracy while improving productivity
Solution Approach 2:
The system creates a copied representation of form data in image-based format rather than converting to symbolic format. This copy maintains the visual integrity of the original forms while allowing for efficient aggregation and querying operations, avoiding the errors inherent in symbolic conversion processes
2Productivity
If symbolic conversion is performed on handwritten stroke information, then data can be processed, but it consumes computing resources that could be used in other ways
Solution Approach 1:
The system creates an image-based copy of form data that can be processed without full symbolic conversion. This approach maintains data processing capability while significantly reducing computing resource consumption by avoiding the resource-intensive OCR/OMR conversion process for aggregation operations
Solution Approach 2:
The system segments the data processing task into two parts: image-based aggregation and querying (which is resource-efficient) and selective symbolic conversion (which is performed only when absolutely necessary). This segmentation reduces overall computing resource consumption while maintaining necessary data processing capabilities
3Reliability
If manual correction of recognition errors is performed, then data accuracy is improved, but it takes up time and requires human intervention
Solution Approach 1:
The image-based document management system acts as an intermediary that preserves data accuracy without requiring manual correction. By maintaining image-based representations that can be directly queried and aggregated, the system eliminates the need for time-consuming manual verification and correction of symbolic conversion errors
Data Source
AI summary
An Image Based Document Management (IBDM) server includes a table generator, a query engine and a user interface engine. The table generator generates a table that includes a label image and at least one field image in a column. The label image represents a column header for the at least one field image. A query engine receives requests to modify the table and in response generates queries to query the table. A user interface engine provides the table for display and modifies the table in response to user input.