Optical Defect Evaluation Using Dual Acquisition and Defect Filtering
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Solution Overview
Problem
Existing methods for evaluating cosmetic defects in optical devices are either costly and time-consuming with human inspection or lack accuracy and repeatability with automatic vision systems, failing to distinguish relevant cosmetic defects from irrelevant ones.
Innovation Solution
A method involving two distinct sets of cosmetic defect acquisition, followed by a subset determination and quality factor calculation, which differentiates defects based on location, type, and position, allowing automatic exclusion of irrelevant defects and enhancing accuracy and repeatability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human inspection is used to evaluate cosmetic defects, then accuracy and repeatability are improved, but cost and time consumption increase
Solution Approach 1:
The patent uses image capture devices to create digital copies (images) of the optical device surfaces, replacing direct human visual inspection. These digital copies are then processed by computer algorithms that simulate and enhance human defect detection capabilities, achieving both high accuracy and automated efficiency.
Solution Approach 2:
The patent replaces the mechanical human inspection system with an automated vision system comprising image capture devices, computer processing units, and algorithmic analysis. This substitution eliminates human time constraints while maintaining or improving defect detection accuracy through consistent, repeatable automated processes.
2Productivity
If automatic vision systems are used to evaluate cosmetic defects, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent employs advanced image processing algorithms that analyze multiple parameters simultaneously (image intensity, gradient, curvature, texture features) to distinguish real cosmetic defects from artifacts or irrelevant surface variations. This multi-parameter analysis enables automated systems to achieve human-level precision in defect identification.
Solution Approach 2:
The system incorporates feedback mechanisms where defect detection results are continuously refined through algorithmic learning and adjustment. The computer processes images through multiple analysis stages, with each stage providing feedback to improve the accuracy of subsequent defect identification, enabling automated systems to achieve high precision comparable to trained human inspectors.
3Reliability
If all detected cosmetic defects are considered, then completeness is improved, but relevance deteriorates due to inclusion of irrelevant defects
Solution Approach 1:
The patent applies different evaluation criteria and weighting to different regions and types of defects on the optical device. The system identifies the location, type, and characteristics of each detected defect, then applies location-specific relevance rules to determine which defects actually impact optical performance. This enables the system to filter out irrelevant defects (such as those in non-critical zones) while maintaining sensitivity to critical defects.
Solution Approach 2:
The patent divides the optical device surface into multiple zones with different defect tolerance levels and applies zone-specific evaluation criteria. By segmenting the analysis into critical and non-critical regions, the system comprehensively detects all defects while selectively focusing attention on those that truly matter for optical performance, eliminating irrelevant information from the final assessment.
Data Source
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AI summary
The invention relates to a method for evaluating cosmetic defects of an optical device, the method comprising: a first acquisition step (S10), during which a first set of cosmetic defects of the optical device is acquired, a second acquisition step (S20) distinct from the first acquisition step (S10), during which a second set of cosmetic defects of the optical device is acquired, the second set of cosmetic defects being different from the first set of cosmetics defects and comprising at least one cosmetic defect corresponding to a cosmetic defect of the first set of cosmetic defects, a subset of cosmetic defects determining step (S30), during which a subset of the first set of cosmetic defects of the optical device is determined based on the comparison of the cosmetic defects of the second set of cosmetic defects and the cosmetic defects of the first set of cosmetic defects, and a quality factor determining step (S80), during which a quality factor of the optical device is determined based on the subset of cosmetic defects.