Superposition Detection in Document Imaging Systems
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Solution Overview
Problem
Document imaging systems often fail to detect and correct superposition scanning defects, leading to errors in scanned documents that can result in suboptimal processing and potential misinterpretation of critical information, such as medical diagnoses.
Innovation Solution
A method and system for analyzing scanned documents to detect superposition defects, identifying affected documents, and notifying users or routing them for re-scanning, utilizing algorithms like the Hough transform for image analysis and metadata processing to determine the number of superimposed documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated scanning is performed without superposition detection, then productivity is improved, but reliability deteriorates due to undetected scanning defects
Solution Approach 1:
The system implements automated feedback by analyzing scanned documents for superposition defects and generating notifications to users. The analysis module detects superposition conditions and feeds this information back through notifications that identify specific documents requiring re-scan, creating a closed-loop quality control system that maintains reliability while preserving automated high-speed scanning.
Solution Approach 2:
The patent introduces an intermediary analysis module between the scanning process and final document output. This module acts as a mediator that automatically detects superposition defects and generates notifications, separating the high-speed scanning function from the quality verification function, thereby maintaining both productivity and reliability.
2Reliability
If manual inspection of scanned documents is performed, then reliability is improved, but productivity deteriorates due to increased processing time
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated image analysis system that uses algorithms to detect superposition defects. The analysis module processes scanned documents automatically, substituting human reviewers with computational methods that maintain high detection accuracy while enabling parallel processing of multiple documents, thus preserving productivity.
Solution Approach 2:
The system implements self-service quality control where the scanning system automatically detects and identifies its own defects through the analysis module. The system serves itself by generating notifications for problematic documents without requiring external manual inspection, thereby maintaining reliability while preserving automated processing throughput.
3Device complexity
If superposition defects are not detected, then device complexity is reduced, but loss of information increases due to undetected errors
Solution Approach 1:
The patent applies preliminary action by detecting superposition defects immediately during the scanning process rather than allowing errors to propagate. The analysis module examines documents as they are scanned and generates notifications before defective documents are processed further, preventing information loss at the source while maintaining relatively simple system architecture through integrated real-time detection.
Data Source
AI summary
A method, computer system, and computer program product for document superposition detection and correction are provided. The embodiment may include receiving a plurality of scanned documents. The embodiment may also include analyzing the plurality of the scanned documents. The embodiment may further include determining if there is a superposition scanning defect within the scanned documents based on the analysis. The embodiment may also include in response to the plurality of the scanned documents containing the superposition scanning defect, identifying a subset of documents within the plurality of scanned documents containing the determined superposition scanning defect. The embodiment may further include transmitting a notification to a user, wherein the notification identifies the subset and that the subset requires a rescan.