Image Feature Matching for Moving Object Recognition
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Solution Overview
Problem
Existing methods for capturing images of moving objects in automated assembly lines fail to accurately recognize the position and orientation of components due to varying illumination conditions and vibrations, leading to potential false recognition and assembly failures.
Innovation Solution
A method that continuously captures images of a moving object and computes image feature values related to positional information and illumination conditions, selecting an image that matches reference values stored in memory to ensure accurate recognition under similar conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are captured while the component is moving at high speed, then productivity is improved, but measurement precision deteriorates due to motion blur and varying illumination conditions
Solution Approach 1:
The system pre-calculates the component's position and orientation based on its movement trajectory before the component actually reaches the measurement position. By predicting where the component will be and what its orientation will be, the system can prepare the measurement parameters in advance, allowing accurate measurement even during high-speed movement without waiting for the component to slow down or stop.
Solution Approach 2:
The measurement system dynamically adjusts its parameters based on the component's real-time movement state. Instead of using fixed measurement parameters, the system continuously updates the expected position and orientation calculations as the component moves, allowing the measurement process to adapt to the dynamic conditions of high-speed assembly while maintaining accuracy.
2Measurement precision
If the robot slows down or stops for image capturing, then measurement precision is improved, but productivity deteriorates due to increased cycle time
Solution Approach 1:
The robot continues its movement and assembly operations without interruption while the measurement system performs its function. The component moves continuously through the workspace, and the measurement system captures and processes images during this continuous motion, eliminating the need for stopping or slowing down the robot, thus maintaining both productivity and measurement capability.
Solution Approach 2:
The system performs measurement calculations in advance based on predicted component positions, allowing the robot to maintain its optimal movement speed and rhythm without being constrained by measurement cycle times. The measurement process is integrated into the continuous workflow rather than being a separate, time-consuming step.
3Adaptability or versatility
If image processing is performed on images captured under varying illumination conditions, then adaptability is improved, but measurement precision deteriorates due to false recognition
Solution Approach 1:
The system pre-calculates the expected position and orientation of the component based on its known movement trajectory and timing. This preliminary calculation provides a reference that is independent of illumination conditions, allowing the measurement system to compare actual images against predicted values and compensate for variations in lighting without being affected by them.
Data Source
AI summary
An image processing method includes acquiring a plurality of image data items by continuously capturing images of an object by an image capturing apparatus (S1), transmitting the plurality of image data items to a computing section (S2), computing image feature values each of which relates to positional information and information correlated with illumination conditions of each of the image data items by using the computing section (S3), comparing degrees of matching between reference image feature values, each of which corresponds to positional information and information correlated with illumination conditions, and the plurality of image data items (S4), and selecting, from the plurality of image data items, an image having positional information and illumination conditions that match the reference image feature values and outputting the image (S5).