Vehicle Camera Calibration Using Equidistant Reference Patterns
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Solution Overview
Problem
Conventional manual calibration of vehicle cameras is prone to errors due to human factors and requires significant computational effort, especially in setting and solving extrinsic parameters for accurate image capture.
Innovation Solution
An automatic calibration reference pattern comprising equidistant characteristic patterns and straight lines, which allows for the identification and conversion of image coordinates between view angle systems, enabling an image conversion method and device to automatically adjust and calibrate vehicle cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is performed by calibration staff, then the camera can be adjusted to satisfy predetermined conditions, but human factors cause image errors and reduce calibration accuracy
Solution Approach 1:
The calibration system performs automatic calibration without human intervention. The calibration staff only needs to place the reference pattern, and the system automatically captures images, identifies characteristic patterns, calculates extrinsic parameters, and completes coordinate conversion. This eliminates human factors such as different observations and carefulness levels that cause calibration errors.
Solution Approach 2:
The manual mechanical adjustment of camera position and direction is replaced by an automated image processing system. The system uses computer vision to identify characteristic patterns in captured images and automatically calculates the transformation parameters, substituting the mechanical manual adjustment process with an automated computational approach.
2Ease of manufacture
If traditional calibration reference patterns are used, then calibration can be performed, but setting and solving extrinsic parameters creates tremendous computational load
Solution Approach 1:
The calibration reference pattern is divided into multiple sub-patterns, each containing characteristic patterns with specific geometric relationships. This segmentation allows the system to identify features more efficiently and reduces the computational complexity of solving extrinsic parameters by breaking down the overall calibration problem into smaller, more manageable sub-problems.
Solution Approach 2:
The invention changes the parameters of the calibration reference pattern by using characteristic patterns with specific geometric properties (equidistant from borders, specific arrangements of straight lines and grid lines). These parameter changes enable more efficient calculation of extrinsic parameters, reducing the computational load while maintaining calibration accuracy.
3Ease of manufacture
If characteristic patterns are not equidistant from borders, then pattern design is simpler, but calibration precision decreases
Solution Approach 1:
The characteristic patterns are designed with specific local quality properties - being equidistant from the borders of the reference pattern. This local geometric property enhances the precision of coordinate identification and calibration accuracy, while the overall pattern design remains systematic and manageable through the use of regular geometric arrangements.
Data Source
AI summary
An image conversion method is provided. An image of a calibration reference pattern is captured. A plurality of first and a plurality of second characteristic patterns of the calibration reference pattern are identified. Coordinates of the first and second characteristic patterns in a first view angle coordinate system are obtained, and coordinates of the first and second characteristic patterns in a second view angle coordinate system are obtained, to obtain a coordinate conversion relationship between the first and second view angle coordinate systems. An input image is converted to an output image according to the coordinate conversion relationship.