Automated Print Defect Detection via Image Registration
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Solution Overview
Problem
High-speed print production systems require efficient defect detection mechanisms to reduce operator intervention and time consumption in identifying and rejecting defective prints, which current systems fail to address effectively.
Innovation Solution
A system that includes physical memory devices and processors to execute print verification logic, registering print medium image data with bitmap data, detecting defects based on predetermined thresholds, computing variance values, and classifying defects as acceptable or unacceptable, thereby automating the defect detection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual operator intervention is used to inspect and reject defective prints, then defect detection accuracy can be maintained, but time consumption increases and productivity decreases
Solution Approach 1:
The patent replaces the mechanical manual inspection system with an automated optical inspection system that uses image capture devices, processors, and algorithms to detect and classify print defects. This substitution maintains high detection accuracy while dramatically increasing inspection speed and productivity.
Solution Approach 2:
The system creates digital copies (images) of the printed medium and analyzes these copies using image processing algorithms to detect defects. This allows rapid automated inspection without physically handling or delaying the actual print production flow.
2Productivity
If automated defect detection is implemented, then productivity increases and operator intervention decreases, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional integrated system where a single automated inspection apparatus performs multiple functions: capturing images of printed material, processing images to detect defects, analyzing defect characteristics, and generating reports. This consolidation reduces overall system complexity compared to having separate manual processes for each function.
Solution Approach 2:
The system is designed to operate autonomously without requiring operator intervention for defect detection and classification. The automated image capture, processing, and analysis functions serve themselves, eliminating the need for manual inspection while maintaining high productivity.
3Measurement precision
If comprehensive defect analysis is performed including variance computation, then defect classification accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary image capture and preprocessing operations while the print production continues. By preparing image data in advance and using efficient algorithms for variance computation and defect analysis, the system minimizes processing time while maintaining high classification accuracy.
Solution Approach 2:
The patent employs sophisticated image processing algorithms that compute variance parameters and other statistical measures to characterize defects. By optimizing these parameter calculations and using them for rapid defect classification, the system achieves high accuracy without excessive processing time delays.
Data Source
AI summary
A method is disclosed. The method includes receiving one or more images of bitmap data applied to a print medium as print medium image data, register the print medium image data to the bitmap data, detecting one or more candidate defects based on whether a difference between the print medium image data at a location and the bitmap data at the location exceeds a predetermined threshold, detecting one or more defects among the candidate defects and transmitting information about the one or more candidate defects classified as defects.