Document Image Segmentation for Efficient Content Retrieval
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Solution Overview
Problem
Current methods for capturing and processing paper documents into electronic format are inefficient, leading to time-consuming error correction, delays, and unnecessary processing of non-relevant content, especially when outsourcing to third-party service bureaus, and do not allow for online indexing and content filtering.
Innovation Solution
A method and system that enables users to segment document images, define metadata fields, and apply filtration criteria to exclude non-relevant objects, allowing for online indexing and efficient content retrieval, with interactive user input for error correction and content management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full-text indexing is performed on all document objects, then complete search capability is achieved, but processing time and resources are excessively consumed
Solution Approach 1:
The patent segments the document image into multiple regions of interest (ROIs) based on user-defined criteria such as text density, object types, or semantic categories. Only these segmented regions are subjected to full-text indexing and detailed processing, while other regions are excluded or processed at a lower level. This segmentation approach maintains search capability for relevant content while dramatically reducing the overall processing scope and time consumption.
2Loss of information
If all image objects are processed for metadata extraction, then comprehensive information is obtained, but processing efficiency decreases due to inclusion of non-relevant content
Solution Approach 1:
The patent extracts and processes only the relevant portions of the document image that contain meaningful information for the user's specific needs. By applying filtration criteria to identify and exclude non-relevant objects and regions, the system obtains sufficient information for effective search and retrieval without the overhead of processing the entire document. This extraction approach balances information completeness with processing efficiency.
3Measurement precision
If user interaction is enabled for content filtering and error correction, then processing accuracy improves, but system complexity increases
Solution Approach 1:
The patent incorporates feedback mechanisms where users can interact with the system to provide corrections, confirmations, or adjustments to the automatically extracted metadata and identified regions of interest. This feedback loop allows the system to learn from user interactions and improve its accuracy over time. The feedback is integrated into the existing processing pipeline in a modular manner, allowing accuracy improvement without proportionally increasing overall system complexity.
Data Source
AI summary
The method includes segmenting a document image to identify image objects within the document image and applying an automatic algorithm to the image objects so as to assign initial metadata to the image objects. The method further includes selecting image objects from the set of image objects whose metadata satisfy filtration criteria so as to exclude those selected image objects from processing and processing a rest of the image objects in the set of image objects. The method further includes presenting the document image, image objects, and metadata to the user and enabling input from the user to manage the image objects, subsets, and metadata.