Image Table Generation for Spanning Layout AI Training
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Solution Overview
Problem
Existing methods for generating image tables are cumbersome and difficult for machines to parse due to complex structures, empty entries, and varied formats, leading to inefficiencies in processing and training of AI models.
Innovation Solution
A method for automatically generating image tables by determining table configurations, providing content templates, and inserting content into cells, while incorporating structural and geometrical information to create accurate and customizable training datasets for AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to generate image tables, then flexibility in creating varied table structures is maintained, but the process becomes cumbersome and error-prone
Solution Approach 1:
The system performs automatic table configuration determination, template selection, and content insertion without requiring manual intervention. The computer automatically generates image tables by processing table data and applying styling rules, eliminating the need for manual creation while maintaining high accuracy and reliability.
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of manually configuring table structures and inserting content, the system uses algorithms to determine table configurations, select appropriate templates, and populate cells automatically, thereby reducing errors and improving efficiency.
2Manufacturing precision
If complex table structures with spanning cells are created manually, then accurate representation of document layouts is achieved, but the complexity of the generation process increases
Solution Approach 1:
The patent divides the table generation process into distinct modular components: table configuration determination, template selection, content insertion, and styling application. Each module handles a specific aspect of table creation, making the overall complex process manageable and systematic while ensuring accurate representation of document layouts including spanning cells.
Solution Approach 2:
The system performs preliminary actions by pre-defining table configurations and content templates before actual table generation. Table structures, spanning cell patterns, and content templates are prepared in advance, allowing the generation process to simply apply these pre-configured elements, thereby reducing the complexity of real-time generation while maintaining structural accuracy.
3Adaptability or versatility
If domain-specific table templates are developed, then recognition accuracy for diverse document types improves, but the initial setup and maintenance effort increases
Solution Approach 1:
The patent creates a universal template system that can handle multiple document domains through a single framework. The table configuration determination module and template selection mechanism are designed to be domain-agnostic, allowing the same system to generate image tables for financial reports, scientific papers, news articles, and other diverse document types without requiring separate specialized tools for each domain.
Solution Approach 2:
The system achieves adaptability across domains by changing parameters within the existing template framework rather than creating entirely new templates. By adjusting table configuration parameters, spanning cell patterns, and content templates, the system can adapt to different document types and domains, reducing the need for extensive template development and maintenance while maintaining broad versatility.
Data Source
AI summary
A method for automatically generating table images includes determining a table configuration including a number of rows of the table, a number of columns of the table and a spanning area of the table, the spanning area indicating a fraction of spanning cells in the table. The table may be generated in accordance with the table configuration. Content may be inserted into cells of the table using a selected content template. An image table of an appearance of the table may be created and the image table may be provided.