Camera Distortion Correction Using Straight-Line Parameter Calibration
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Solution Overview
Problem
Existing methods for calibrating camera systems fail to accurately calculate internal parameters such as optical axis offset and magnification, leading to incorrect distortion correction and impaired angle calculation, which affects the calibration of external parameters and causes straight lines in images to bend, especially when internal parameters change due to factors like thermal expansion.
Innovation Solution
An image processing apparatus and method that corrects distortion in captured images using perspective projection conversion and identifies internal parameters based on straight line edges in the corrected image, employing optimization methods to determine the correct internal parameters of the image capturing apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distortion correction is performed using conventional methods, then processing speed is improved, but measurement precision of internal parameters deteriorates
Solution Approach 1:
The patent replaces conventional mechanical/calibration-based distortion correction methods with a computational approach using perspective projection conversion. The generation unit performs distortion correction by calculating transformation based on captured images and determining internal parameters through optimization algorithms, substituting physical calibration procedures with mathematical computation to achieve both speed and precision.
Solution Approach 2:
The patent changes the approach from fixed calibration parameters to dynamically determined internal parameters. The obtainment unit calculates internal parameters (focal length, optical center) by optimizing the fit between perspective-projected 3D points and actual 2D image points, allowing parameters to be precisely determined for each imaging condition rather than relying on pre-set values.
2Device complexity
If internal parameters are not accurately determined, then device complexity is reduced, but manufacturing precision of image correction deteriorates
Solution Approach 1:
The system performs self-calibration by automatically determining its own internal parameters from captured images. The obtainment unit uses the captured image data to calculate internal parameters through optimization, eliminating the need for external calibration equipment or complex manual adjustment mechanisms, thus maintaining low device complexity while achieving high correction precision.
Solution Approach 2:
The patent implements an iterative optimization process where the system continuously refines internal parameter values by comparing perspective-projected points with actual image points. This feedback loop allows the system to self-correct and converge on accurate parameter values without requiring complex external calibration systems.
Data Source
AI summary
An image processing apparatus generates a corrected image to correct distortion in a captured image shot by an image capturing apparatus and obtains an internal parameter of the capturing apparatus based on a straight line edge in the corrected image. For parameter candidates serving as correct candidates for the internal parameter, a corrected image is generated by performing a perspective projection conversion on the captured image using the parameter candidate. One of the plurality of parameter candidates is obtained as the internal parameter of the capturing apparatus based on a straight line edge in each corrected image. For each of a plurality of rotated images obtained by rotating the corrected image by different rotation angles, obtained are a length of a vertical straight line edge in the rotated image, an evaluation value becoming higher as a total of the lengths obtained increases, and a parameter candidate providing a highest evaluation.