Camera Motion Blur Measurement Using Mass-Adaptive Vibration
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Solution Overview
Problem
Existing methods for evaluating the image stabilization function of cameras lack accuracy in measuring motion blur, particularly due to variations in camera shake caused by the camera's mass, which affects the vibration patterns during image capture.
Innovation Solution
A measurement method involving a vibratory apparatus that simulates camera shake by vibrating a table with the camera, using selected vibration data based on the camera's mass to accurately measure motion blur by acquiring and analyzing images taken during these vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is fixed on a vibratory table to measure motion blur, then measurement precision is improved, but device complexity increases due to the need for mass-based vibration data selection
Solution Approach 1:
Vibration data corresponding to different camera masses is pre-calculated and stored in the storage unit before measurement. This allows the measurement system to directly retrieve appropriate vibration data based on the camera's mass without performing complex real-time calculations, thereby improving measurement precision while managing device complexity through pre-computation.
Solution Approach 2:
A mass detection unit is introduced as an intermediary component to automatically detect the camera's mass and select the corresponding vibration data from storage. This intermediary mechanism simplifies the overall system by automating the data selection process based on mass, resolving the contradiction between measurement precision and device complexity.
2Measurement precision
If vibration data is selected based on camera mass, then measurement precision is improved, but ease of operation deteriorates due to additional mass detection and data selection steps
Solution Approach 1:
The measurement system performs self-service by automatically detecting the camera's mass through the mass detection unit and autonomously selecting the corresponding vibration data from storage. This automation eliminates the need for manual mass input or selection by the operator, thereby maintaining ease of operation while achieving mass-based precision measurement.
Solution Approach 2:
The system implements feedback through the mass detection unit that continuously monitors the camera's mass and adjusts the vibration data selection accordingly. This closed-loop feedback mechanism ensures that the appropriate vibration data is automatically applied based on the actual camera mass, improving measurement precision without requiring complex manual intervention from the operator.
3Measurement precision
If multiple vibration data sets are stored for different camera masses, then measurement precision is improved, but loss of information increases due to larger storage requirements
Solution Approach 1:
Vibration data is segmented into multiple discrete data sets, each corresponding to a specific camera mass range. This segmentation allows the storage unit to efficiently organize and retrieve only the relevant vibration data for the detected camera mass, improving measurement precision while minimizing storage space consumption by avoiding the need to store all possible vibration data variations.
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 allows for precise measurement of motion blur, reflecting real-world camera shake scenarios and providing a high accuracy assessment of image stabilization performance.
Implementation Method 1
vibrating the vibratory table of the vibratory apparatus in accordance with the selected vibration data
Data Source
AI summary
A measurement method capable of measuring a motion blur amount of an image with a high accuracy is provided. The measurement method fixes a camera on a vibratory table of a vibratory apparatus; selects one of a plurality of pieces of vibration data in accordance with the mass of the camera; shakes the vibratory table of the vibratory apparatus in accordance with the selected vibration data; acquires an evaluation image by imaging a subject by the camera while the vibratory table is being shaken; and measures a motion blur amount of an image based on the acquired evaluation image. In this case, the vibration data may be obtained by performing statistic processing for measured data.