Gestalt-Based Document Location Identification
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Solution Overview
Problem
Current image recognition technologies face challenges in accurately identifying locations within documents, especially under poor lighting conditions or when the image quality is low, and require skilled users.
Innovation Solution
A software and hardware facility that utilizes gestalt information to recognize places or locations in documents by comparing captured images to an index of text and layout information, extracting features such as space distances, character densities, and textual features, and employing iterative processing and context analysis to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current image recognition techniques are used to identify locations in documents, then the system can recognize text and images, but the recognition accuracy deteriorates under poor lighting conditions, low image quality, or when used by unskilled users
Solution Approach 1:
The patent segments the document image into multiple regions (text regions, image regions, table regions) and processes each region separately using region-specific recognition algorithms. This segmentation allows the system to focus computational resources on identifying distinctive features in each region type, improving location identification accuracy even under poor imaging conditions.
Solution Approach 2:
The system performs preliminary indexing of document locations based on gestalt information (layout patterns, text density, spacing) before actual recognition is needed. This pre-processing creates a reference framework that guides subsequent image recognition, enabling accurate location identification even when the captured image quality is low or lighting is poor.
2Measurement precision
If detailed image analysis is performed to improve location identification accuracy, then recognition precision improves, but processing time and computational complexity increase
Solution Approach 1:
The patent applies partial action by performing detailed analysis only on critical regions that require precise location identification, while using simpler methods for less critical areas. The system selectively applies complex recognition algorithms based on the importance and type of each document region, achieving high accuracy for key locations without the full computational cost of analyzing every pixel throughout the entire document.
Solution Approach 2:
By pre-computing and storing gestalt information about document layout and structure during an indexing phase, the system avoids performing detailed analysis during actual recognition queries. This preliminary action creates a reference model that enables fast, accurate location identification without repeating computationally intensive processing.
3Measurement precision
If the system requires skilled users to operate image recognition effectively, then recognition accuracy improves, but ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing document structure, identifying regions of interest, and selecting appropriate recognition algorithms without user intervention. The gestalt-based indexing and automatic region classification enable the system to adapt to different document types and qualities autonomously, maintaining high accuracy while requiring minimal user skill or input.
Solution Approach 2:
The system performs preliminary analysis of document characteristics and pre-configures recognition parameters based on detected document type and quality. This automatic adaptation eliminates the need for users to manually adjust settings or understand complex recognition options, making the system easy to operate while maintaining high accuracy through automated optimization.
Data Source
AI summary
A facility for identifying a location in a printed document is described. The facility obtains an image of the printed document, and extracts gestalt information from text occurring in the image of the printed document. The facility compares the extracted gestalt information to an index of documents and, based upon this comparison, identifies a document that includes the gestalt information.