Scanned Image Artifact Characterization and Repair System
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Solution Overview
Problem
Document conversion systems face challenges due to physical media damage and artifacts from photocopies, leading to errors, inefficiencies, and increased costs in processing and transmitting scanned images.
Innovation Solution
A scanned image processing system that characterizes artifacts in scanned images and modifies them based on user-configurable parameters, including removing or repairing damage such as staples, holes, tears, and folds, to improve image quality and reduce storage and transmission costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scanned images are processed as-is without artifact removal, then processing speed is maintained, but image quality deteriorates and errors increase
Solution Approach 1:
The system performs artifact characterization and image modification before the scanned images are used for processing. By pre-identifying and pre-repairing artifacts such as staples, holes, tears, and folds, the system ensures high image quality is achieved ahead of time, allowing subsequent processing operations to proceed efficiently without rework.
Solution Approach 2:
The artifact characterizer and image modifier operate automatically on scanned images without requiring manual intervention. The system self-characterizes artifacts by analyzing image patterns and self-modifies the images by applying repair algorithms, thereby maintaining high processing speed while improving image quality through automated means.
2Reliability
If artifact characterization and modification are performed, then image quality improves, but processing time increases
Solution Approach 1:
The system replaces manual inspection and repair processes with automated computational algorithms. The artifact characterizer uses image processing algorithms to automatically detect and characterize artifacts, while the image modifier uses computational algorithms to automatically repair or remove them, thereby reducing processing time compared to manual methods while maintaining high image quality.
Solution Approach 2:
The system modifies image parameters such as pixel values, contrast, and sharpness dynamically during the artifact removal process. By changing these parameters adaptively based on the characterized artifacts, the system achieves high image quality restoration efficiently, minimizing the time required compared to static processing methods.
3Ease of operation
If damaged documents are processed manually, then flexibility is maintained, but cost and error rate increase
Solution Approach 1:
The automated system performs artifact characterization and image modification without requiring manual intervention. The artifact characterizer automatically identifies damaged areas and the image modifier automatically applies repairs, maintaining operational flexibility while significantly reducing error rates associated with manual processing of damaged documents.
Solution Approach 2:
The system incorporates feedback loops where the artifact characterizer continuously analyzes the scanned image, identifies artifacts, and provides characterization data to the image modifier. This feedback mechanism ensures that repairs are accurately targeted and executed, reducing errors while maintaining the flexibility to handle various types of document damage.
Data Source
AI summary
A scanned image processing system, a method of processing scanned images and a document conversion system incorporating the scanned image processing system or the method. In one embodiment, the scanned image processing system includes: (1) an artifact characterizer configured to provide a characterization of at least one artifact on at least one of obverse and reverse scanned images of a page and (2) an image modifier associated with the artifact characterizer and configured to modify at least one of the obverse and reverse scanned images based on the characterization and at least one operating parameter.