Adaptive Image Capture for Motion Blur Reduction
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Solution Overview
Problem
Automated visual inspection in production lines is hindered by blurry images caused by motion, which affects defect detection and quality assurance, as existing systems struggle to capture high-quality images with minimal or no motion.
Innovation Solution
A system and method that learn motion patterns from previous images to determine optimal times for capturing images with low or no motion, and utilize motion detection to inform users on how to eliminate motion, thereby facilitating high-quality image capture for inspection tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are captured continuously during production line inspection, then productivity is improved, but image quality deteriorates due to motion blur
Solution Approach 1:
The system dynamically adjusts the image capture timing based on real-time motion detection. The camera captures images only when motion is below a threshold level, making the capture process adaptive to the dynamic conditions on the production line. This resolves the contradiction by making the inspection system flexible rather than rigid, allowing high-speed operation while maintaining image quality.
Solution Approach 2:
The system uses motion detection feedback to control the image capture process. Motion is continuously monitored and this information feeds back to the camera control system, which adjusts capture timing accordingly. This closed-loop feedback mechanism ensures that images are captured at optimal moments, maintaining both productivity and image quality.
2Measurement precision
If motion detection and analysis systems are added to identify optimal capture timing, then image quality is improved, but device complexity increases
Solution Approach 1:
The motion detection system serves multiple functions: it detects motion for timing optimization, provides feedback for capture control, and can potentially guide production line adjustments. By making the motion detection component multi-functional, the system achieves improved image quality without proportionally increasing complexity, as the same hardware serves multiple purposes.
Solution Approach 2:
The system uses the existing production line motion characteristics to automatically determine optimal capture timing without requiring external intervention or complex manual configuration. The motion detection system self-adjusts based on the actual conditions observed, reducing the need for additional complex control mechanisms.
3Measurement precision
If image capture timing is optimized based on motion patterns, then image quality is improved, but loss of time occurs in motion analysis and timing calculation
Solution Approach 1:
The system performs preliminary motion pattern analysis during periods when images are not being captured, such as between production items or during idle moments. By preparing motion models and predictions in advance, the system minimizes processing time during actual capture moments, thus improving image quality without significant time loss.
Solution Approach 2:
The motion detection and analysis operates continuously in the background alongside the production line, rather than interrupting the capture process. This allows the system to maintain continuous monitoring and analysis while capturing images at optimal moments, eliminating idle time and ensuring that the time investment in motion analysis does not reduce overall productivity.
Data Source
AI summary
Embodiments of the invention provide a visual inspection process in which motion is detected in an image of an item on an inspection line and the origin of the motion is determined. Determining the origin of motion in an image enables to provide a user with specific and clear indications on how to eliminate motion in the images and thus facilitates the visual inspection process.