Interference Image Compensation in Optical Displacement Sensors
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Solution Overview
Problem
Existing optical displacement estimating apparatuses face inaccuracies in displacement estimation due to interference images caused by objects like scraping traces, fingerprints, or dust on the detecting surface, requiring additional hardware or complex algorithms to resolve.
Innovation Solution
A method and apparatus that utilize image characteristics from current frames to determine and update interference images without additional hardware or complex algorithms, using a processing unit to illuminate objects, capture frames, and store interference images, allowing for simple computation and compensation of interference effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extra hardware or complicated algorithms are used to solve interference images, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system uses the sensor's own captured frames to identify and compensate for interference images. By analyzing image characteristics from the current frame and comparing with the defined interference image, the system performs self-diagnosis and self-correction without requiring external assistance or additional hardware components.
Solution Approach 2:
The interference image is pre-defined and stored in the storage apparatus before actual displacement measurement begins. This preliminary characterization of interference patterns allows the system to quickly compare and compensate for interference during operation, avoiding the need for complex real-time analysis or additional hardware.
2Device complexity
If simple computation is used to determine interference images, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system creates a copy or model of the interference image pattern by storing it in the storage apparatus. This copied interference model can be repeatedly used for comparison and compensation without requiring complex real-time computation, thus maintaining both simplicity and accuracy.
Solution Approach 2:
The interference image characteristics are pre-computed and stored before actual measurement. This preliminary action transfers the computational burden to an offline stage, allowing simple comparison operations during real-time displacement estimation while maintaining high precision.
3Device complexity
If interference images are not compensated, then device complexity is reduced, but measurement precision deteriorates due to inaccurate displacement estimation
Solution Approach 1:
The system extracts the interference image component from the captured frame by comparing it with the defined interference image stored in the storage apparatus. This extracted interference information is then compensated for, allowing the remaining valid image data to be used for accurate displacement estimation without requiring complex overall processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate displacement estimation by removing interference images through image compensation, reducing hardware costs and computational complexity, and maintaining precision without the need for extra hardware or intricate algorithms.
Implementation Method 1
controlling a light source to illuminate an object on a detecting surface to generate an image
Implementation Method 2
controlling a sensor to catch a current frame of the image
Data Source
AI summary
A computer readable media having at least one program code recorded thereon. An interference image determining method can be performed when the program code is read and executed. The interference image determining method comprises: (a) controlling a light source to illuminate an object on a detecting surface to generate an image; (b) controlling a sensor to catch a current frame of the image; (c) utilizing an image characteristic included in the current frame to determine a interference image part of the current frame; and (d) updating a defined interference image according to the determined interference image part.