Document Image Fingerprinting for Predictive Structural Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital document analysis methods lack efficiency and reliability in performing predictive structural analysis, particularly in identifying similarities across document image data objects, which hampers the processing of search queries and document image server systems.
Innovation Solution
The use of spatial fingerprint, object fingerprint, and semantic fingerprint document image pair distance measures, combined with deep learning techniques and graph theory, to determine dimension-wise bounding box pair distance measures and cross-graph document image pair distance measures, enabling the generation of predicted document image pair distance measures for performing prediction-based actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional digital document analysis methods are used, then the system is simpler to implement, but the computational efficiency and reliability of predictive structural analysis deteriorates
Solution Approach 1:
The patent segments document image analysis into multiple fingerprint components (spatial, object, and semantic fingerprints), each handling specific aspects of document comparison. This segmentation allows the system to process complex documents through modular, specialized sub-tasks, improving computational efficiency while maintaining manageable system complexity through division of labor among different fingerprinting modules.
Solution Approach 2:
The patent introduces multi-dimensional analysis by creating spatial fingerprints based on coordinate information, object fingerprints based on structural relationships, and semantic fingerprints based on content meaning. This dimensional expansion transforms the analysis from simple image comparison to multi-layered feature space comparison, significantly improving predictive structural analysis efficiency and reliability.
2Measurement precision
If simple image comparison methods are used, then the system is faster to implement, but the accuracy in identifying similar document images deteriorates
Solution Approach 1:
The patent performs preliminary fingerprint extraction and dimension-wise bounding box pair distance measure graph construction before actual document comparison. By pre-processing documents into structured fingerprint representations with spatial, object, and semantic features, the system enables faster and more accurate similarity detection during query processing, reducing processing time while improving accuracy.
Solution Approach 2:
The patent transforms document images into multiple parameter representations including spatial coordinates, object relationships, and semantic features. By changing from raw pixel comparison to multi-parameter fingerprint comparison, the system achieves higher measurement precision in identifying similar documents while the structured parameter organization enables efficient computation.
3Reliability
If comprehensive document analysis is performed, then the reliability of predictive structural analysis is improved, but the computational resources required increase
Solution Approach 1:
The patent implements a hierarchical fingerprinting approach where spatial, object, and semantic fingerprints are generated selectively based on document type and query requirements. This partial action strategy ensures comprehensive analysis when needed for high reliability, while allowing resource optimization by computing only necessary fingerprint types for specific tasks, balancing reliability with computational resource consumption.
Data Source
AI summary
Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform digital document analysis using at least one of spatial fingerprint document image pair distance measures for document image pairs, object fingerprint document image pair distance measures for document image pairs, and semantic fingerprint document image pair distance measures for document image pairs.