Print Quality Diagnosis via Pattern Extraction
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Solution Overview
Problem
The print quality of image forming apparatuses degrades over time, requiring expert intervention for diagnosis and correction, which is inefficient and costly.
Innovation Solution
The image forming apparatus determines and corrects print quality by rendering a print job, extracting pattern information, and scanning the output to detect diagnostic items, transmitting results to a server for analysis and receiving correction measures, allowing for automated quality assessment and improvement without expert intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expert technicians manually diagnose and correct print quality, then diagnostic accuracy is improved, but labor cost and time consumption increase
Solution Approach 1:
The image forming apparatus automatically performs self-diagnosis by extracting pattern information from rendered images and comparing it with reference data, eliminating the need for expert technicians to manually diagnose print quality issues. The system serves itself by autonomously identifying degradation patterns and determining corrective actions.
Solution Approach 2:
The patent replaces the mechanical/manual diagnostic process with an automated image processing and pattern recognition system. Instead of technicians visually inspecting and analyzing printed patterns, the system uses automated extraction of pattern information from rendered images and digital comparison with reference data to determine print quality status.
2Reliability
If expert technicians are deployed for print quality diagnosis, then diagnostic capability is improved, but operational cost increases
Solution Approach 1:
The image forming apparatus performs autonomous self-diagnosis using built-in pattern recognition algorithms, eliminating the need to deploy paid expert technicians. The system automatically extracts pattern information from rendered images, compares it with reference data, and determines corrective actions without human intervention, thereby reducing operational costs while maintaining diagnostic capability.
Solution Approach 2:
The patent introduces an automated pattern recognition system as an intermediary between the print quality degradation and the corrective action. This intermediary system processes pattern information from rendered images and translates it into diagnostic results, replacing the need for expert technicians as intermediaries and reducing operational costs.
3Productivity
If automated pattern recognition is implemented, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The patent extracts only the essential pattern information from rendered images that is relevant to print quality diagnosis, rather than processing the entire image or using complex general-purpose AI models. By selectively extracting specific pattern features and comparing them with reference data, the system achieves automated diagnosis with relatively simple processing logic.
Solution Approach 2:
The system applies different processing strategies to different parts of the diagnostic process: it extracts specific pattern information from rendered images using targeted algorithms, compares extracted patterns with reference data using predefined criteria, and determines corrective actions based on localized pattern mismatches. This localized approach to pattern recognition simplifies the overall system complexity while maintaining operational efficiency.
Data Source
AI summary
An example image forming apparatus includes an image forming apparatus, a processor, and a memory storing instructions executable by the processor. The processor of the image forming apparatus executes the instructions to render a print job, obtain information regarding a pattern for determining print quality from a rendered image of the print job, scan, through the image forming job unit, a document on which the rendered image is printed, and determine the print quality based on a scanned image of the document and the obtained information regarding the pattern.