Optical Lens Edge Detection Neural Network Defect Inspection
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Solution Overview
Problem
Current automatic defect inspection technologies for electronic components have high error rates, necessitating double human verification, which reduces efficiency and reliability in mass production.
Innovation Solution
An optical inspection method and system that uses an optical lens and processing circuit to perform edge detection and defect inspection based on a neural network architecture, improving defect pattern identification accuracy by transforming raw images into edge pattern images for enhanced analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic defect inspection is performed using conventional optical methods, then inspection speed and productivity are improved, but inspection accuracy deteriorates due to high error rates
Solution Approach 1:
The inspection process is segmented into distinct stages: edge detection to extract edge patterns from images, followed by defect inspection using neural networks on the extracted edge patterns. This segmentation allows each stage to be optimized independently, improving overall accuracy while maintaining automation speed.
Solution Approach 2:
Edge patterns serve as an intermediary representation between the original image and the defect inspection process. By extracting and analyzing edge patterns as an intermediate step, the system achieves higher inspection accuracy while maintaining automated processing speed.
2Measurement precision
If human employees perform visual confirmation inspection, then inspection accuracy is improved, but productivity decreases due to manual verification requirements
Solution Approach 1:
The inspection system performs self-verification through neural network-based defect inspection on extracted edge patterns, eliminating the need for human double-checking. The automated system validates its own inspection results, maintaining high accuracy while improving productivity.
3Device complexity
If conventional defect inspection methods are used, then device complexity is reduced, but reliability deteriorates due to high error rates requiring human verification
Solution Approach 1:
Edge detection is performed as a preliminary action before defect inspection. By pre-processing images to extract edge patterns, the system improves reliability of the subsequent defect inspection while adding only one processing stage, maintaining relative system simplicity.
Data Source
AI summary
An optical inspection method for an optical inspection device comprising an optical lens is provided according to an embodiment of the disclosure. The optical inspection method includes: obtaining a first image of an object by the optical lens; performing an edge detection on the first image to obtain a second image comprising an edge pattern; and performing a defect inspection operation on the second image based on a neural network architecture to inspect a defect pattern in the second image. In addition, an optical inspection device and an optical inspection system are provided according to embodiments of the disclosure.