Graph-Based Text Block Segmentation for Coherent Document Layouts
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Solution Overview
Problem
Existing text block segmentation algorithms fail to produce optimized layouts across different regions of a document page, leading to difficulties in further analysis and processing due to inconsistent segmentation of coherent text blocks.
Innovation Solution
Adaptive text block segmentation algorithms that utilize a graph-based approach to determine optimal segmentation patterns by comparing semantic information with predefined types, calculating a confidence degree, and adjusting segmentation based on predetermined thresholds to ensure coherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single text block segmentation algorithm is used for the entire page, then the processing is simple and fast, but the segmentation quality is inconsistent across different regions
Solution Approach 1:
The patent applies local quality by using different text block segmentation algorithms for different regions of the page. The page is divided into multiple regions, and each region can utilize a segmentation algorithm best suited to its characteristics, thereby improving overall segmentation quality while managing complexity through regional specialization.
Solution Approach 2:
The patent implements dynamics by adaptively selecting segmentation algorithms based on region characteristics. Rather than using a fixed algorithm for the entire page, the system dynamically chooses appropriate algorithms for each region based on the specific features and requirements of that region, optimizing segmentation quality adaptively.
2Manufacturing precision
If multiple segmentation algorithms are used for different regions, then segmentation quality improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies segmentation by dividing the page into multiple regions and applying appropriate algorithms to each. This regional segmentation allows for optimized processing where each region can be handled with the most suitable algorithm, improving overall segmentation consistency while managing computational overhead through targeted application of complex algorithms only where needed.
Data Source
AI summary
A computer-implemented method for text block segmentation includes determining a first text block segmentation pattern utilized to generate a segmented text block based, at least in part, on a comparison of semantic information associated with the segmented text block and a plurality of predefined types of text block segmentation patterns indicated by a graph; calculating a first degree of confidence in a size of the segmented text block based, at least in part, on comparing semantic entities associated with the segmented text block with semantic entities indicated by leaf nodes stemming from a first non-leaf node included in the graph and representative of the first type of text block segmentation pattern; and determining that the size of the segmented text block is non-optimal based on the calculated degree of confidence in the size of the segmented text block being below a predetermined threshold.