Graphics Correction Engine for Automated Image Quality Control
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Solution Overview
Problem
Current systems for uploading images to product design websites lack the ability to test image quality and automatically correct issues, leading to user dissatisfaction and inability to utilize the images for intended purposes due to lack of feedback and correction capabilities.
Innovation Solution
A web-based graphics correction engine with a content testing module, content processing module, and communications means that receives uploads, determines properties, analyzes against threshold information, and provides feedback and automatic corrections to ensure image quality meets printing standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system provides only error messages without correction capabilities, then the system complexity remains low, but the ease of operation deteriorates because users cannot correct image issues themselves
Solution Approach 1:
The system automatically analyzes uploaded images, identifies quality issues, and performs corrections without requiring user intervention. The correction engine autonomously detects problems such as low resolution, incorrect formatting, or quality thresholds not being met, and applies appropriate fixes, allowing the system to serve itself rather than requiring user expertise for image correction
Solution Approach 2:
A correction engine is introduced as an intermediary component between the image upload function and the final product generation. This intermediary automatically processes images, provides feedback on quality issues, and performs corrections, thereby bridging the gap between simple upload functionality and complex image correction requirements without exposing users to the complexity
2Productivity
If the system automatically corrects images, then the productivity increases by reducing manual correction needs, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system performs image analysis and correction actions automatically at the time of upload, before the user proceeds with product creation. By conducting quality checks and applying corrections in advance, the system eliminates the need for later manual interventions, thereby increasing overall productivity without requiring users to understand complex correction processes
Solution Approach 2:
The correction engine operates autonomously to detect and fix image quality issues without requiring user involvement. It automatically compares uploaded images against quality standards, identifies deficiencies, and applies corrections, thereby streamlining the workflow and improving productivity while encapsulating the complexity within the automated system
3Measurement precision
If the system provides detailed feedback on image properties, then the measurement precision improves, but the loss of information increases due to the complexity of presenting multiple properties
Solution Approach 1:
The system extracts only the most relevant image quality issues from the full set of analyzed properties and presents them to the user as actionable feedback. Instead of overwhelming users with all measured properties, it selectively outputs only those properties that require attention or correction, thereby maintaining measurement precision while preventing information overload
Solution Approach 2:
The system implements a structured feedback mechanism that provides users with specific, actionable information about image quality issues. It analyzes multiple image properties with high precision but presents feedback in a simplified format that highlights only the critical issues needing correction, thereby maintaining measurement accuracy while improving information delivery
Data Source
AI summary
The present invention generally relates to graphic correction systems and methods. In particular, embodiments of the invention are directed to systems and methods configured to test the quality of images or other multimedia content uploaded to a web-based application and automatically performing corrections and conversions to the image or other multimedia content based at least in part on the results of the quality test.