Automated Image Defect Detection and Correction Preview
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Solution Overview
Problem
Current multifunction devices lack automated defect detection and correction capabilities for scanned images, leading to increased productivity costs and delayed defect identification, as users only become aware of errors upon reviewing hard copies, affecting both productivity and recipient users.
Innovation Solution
A method and system for automated image defect correction using a processor to analyze input image data, detect defects such as skew, contamination, and banding, generate representations with indicia, and allow users to correct these defects through a user interface, enabling real-time preview and correction of scanned images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated defect detection and correction is implemented, then productivity is improved and time is saved, but device complexity increases
Solution Approach 1:
The system performs automated self-diagnosis and self-correction of image defects. The processor automatically detects defects in scanned images and applies corrections without requiring manual user intervention, allowing the device to serve itself in maintaining image quality.
Solution Approach 2:
The system provides visual feedback to the user by displaying a representation of the scanned image with indicia marking detected defects. This feedback loop allows users to review and confirm corrections, or request re-scanning if needed, improving productivity while maintaining controlled complexity.
2Loss of time
If manual review of hard copies is required to detect defects, then device complexity remains low, but loss of time increases and productivity decreases
Solution Approach 1:
The system performs defect detection and correction during the scanning process itself, before the user needs to review or use the image. By detecting and correcting defects preliminarily, the system eliminates the need for time-consuming manual review of hard copies.
Solution Approach 2:
The patent replaces the mechanical process of manually reviewing hard copies with an automated electronic defect detection and correction system. The processor analyzes image data and applies corrections electronically, substituting manual mechanical review with automated digital processing.
3Manufacturing precision
If defects are not detected until hard copy review, then device complexity is low, but manufacturing precision of image output deteriorates
Solution Approach 1:
The system introduces an intermediary defect detection and correction layer between the scanning process and final image output. This intermediary processor analyzes the scanned image data, identifies defects, and applies corrections before the image is finalized or transmitted, ensuring high manufacturing precision.
4Loss of information
If scan to email operation is used, then productivity is improved by eliminating manual handling, but loss of information occurs as errors are not apparent to the sender
Solution Approach 1:
The system provides feedback to the sender by displaying a representation of the scanned image with indicia marking detected defects. This allows the sender to see what errors or defects exist in the image before it is emailed, preventing loss of information about image quality issues.
Solution Approach 2:
The system performs preliminary defect detection and correction before the image is transmitted via email. By identifying and correcting defects in advance, the system ensures that the transmitted image is of high quality without requiring the recipient to notice errors.
Data Source
AI summary
As set forth herein, methods and systems for automated image defect detection. An input image is subjected to skew detection and contaminant detection. Upon detection of skew of and/or contaminants in the image data, correction data, including indicia of the contaminants/skew, correction angles and directions are calculated and displayed on an electronic representation of the document. Automatic correction may then be performed to correct the detected defects, allow the defects to remain, or re-scan the original document to generate new image data without the detected defects.