Camera Calibration Coverage Feedback for Multi-Lens Image Alignment
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Solution Overview
Problem
Conventional image calibration methods for cameras, particularly multi-lens cameras, are time-consuming due to the need to consider viewing angles and lens distortions, leading to inefficiencies in the image stitching process.
Innovation Solution
An image calibration system and method that automatically determines the need for additional image captures based on incomplete coverage, using a processor to control camera modules mounted on a movable plate to adjust the line of sight, ensuring sufficient qualified images are obtained without adhering to predetermined angles, thereby adapting to various types of image capturing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image calibration flow is used for multi-lens cameras, then image alignment quality is improved, but calibration time increases significantly
Solution Approach 1:
The system automatically determines whether captured images are sufficient for calibration by having the processor analyze the captured images themselves. The processor evaluates image quality metrics and decides whether additional images are needed, eliminating the need for manual intervention or predetermined calibration protocols.
Solution Approach 2:
The system changes from fixed predetermined calibration angles to dynamic angle selection based on actual image capture quality. The processor adjusts calibration parameters adaptively by evaluating whether captured images meet quality thresholds, allowing flexibility in capture angles while maintaining alignment precision.
2Manufacturing precision
If predetermined capture angles are followed during calibration, then calibration completeness is improved, but adaptability to different camera types deteriorates
Solution Approach 1:
The system transitions from static predetermined angles to dynamic angle selection. The processor dynamically determines capture angles based on the specific camera module being calibrated and the quality of captured images, allowing the same system to adapt to different camera types while ensuring complete calibration coverage.
Solution Approach 2:
The calibration process is segmented into individual camera module calibrations. The processor handles each camera module separately, determining appropriate capture angles and image sufficiency for each module independently, which enables adaptation to different camera configurations while maintaining overall calibration completeness.
3Measurement precision
If multiple images are captured from different angles, then calibration accuracy is improved, but operation complexity increases
Solution Approach 1:
The processor continuously evaluates captured images to determine whether sufficient quality images have been obtained. This feedback mechanism automatically controls whether additional images need to be captured, simplifying the operation by eliminating the need for operators to manually plan multiple capture angles while still achieving high calibration accuracy.
Data Source
AI summary
An image calibration system including an image capturing device, a calibration unit, a mount plate, and a processor are provided. The image capturing device includes at least one camera module. The processor is configured to: control the at least one camera module to capture an image of the calibration unit; determine whether there is any other part of the calibration unit not captured yet based on images already captured by the at least one camera module; and in response to determining that there is at least a part of the calibration unit not shown in the captured images, control the at least one camera module to capture another image of the calibration unit. The processor further calculates image calibration parameters based on a sufficient number of qualified images captured by the at least one camera module. The image calibration parameters are used for calibrating image distortion.