Selective Distortion Correction for Vehicle Imaging Systems
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Solution Overview
Problem
Existing image processing systems for vehicle safety face a time lag due to the need for distortion correction in images captured by fish-eye lenses, which delays obstacle recognition and subsequent control actions.
Innovation Solution
An image processing apparatus that selectively performs distortion correction on areas of an image with significant distortion, while skipping correction on areas with minimal distortion, allowing for early recognition of objects both near and far from the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distortion correction is performed on the entire image, then image accuracy is improved, but processing time increases
Solution Approach 1:
The image is divided into multiple regions based on distortion characteristics: a first region with significant distortion that requires correction, and a second region with minimal distortion that can be processed without correction. This segmentation allows the system to apply distortion correction selectively only where needed, reducing overall processing time while maintaining image accuracy in critical areas.
Solution Approach 2:
Different processing approaches are applied to different regions of the image based on their specific distortion characteristics. The first region undergoes full distortion correction to ensure accuracy, while the second region is processed more quickly without correction since its distortion is minimal. This local quality approach optimizes the balance between image accuracy and processing efficiency.
2Measurement precision
If distortion correction is performed on the entire image, then image quality is improved, but processing speed decreases
Solution Approach 1:
The image processing is segmented into different regions with different distortion characteristics. By identifying and separating the first region (high distortion) from the second region (low distortion), the system can apply appropriate processing to each, maintaining image quality where needed while improving overall processing speed.
Solution Approach 2:
Instead of applying distortion correction to the entire image (excessive action), the system applies correction only to the extent necessary - specifically to the first region where distortion is significant. This partial action approach maintains sufficient image quality for obstacle recognition while significantly improving processing speed.
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 reduces the time required for distortion correction, enabling faster recognition of objects ahead of the vehicle and improving vehicle safety by allowing for quicker response times in collision avoidance systems.
Implementation Method 1
a free-curved surface lens configured to form an image on the imaging element, wherein the image includes a first area having a distortion that increases with increasing distance from a center
Data Source
AI summary
An image processing apparatus is provided with: an acquirer configured to obtain an image including a first area and a second area, wherein the first area has a distortion that increases with increasing distance from an image center and the second area is in a predetermined angle range with respect to a straight line passing through the image center and extending in a horizontal axis, and the second area has a smaller distortion than that of the first area; and a corrector configured to perform a distortion correction process on the first area and but not to perform the distortion correction process on the second area.