Lane Detection Analysis Region Determination
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Solution Overview
Problem
Current lane detection methods in autonomous driving and advanced driver assistance systems are inefficient due to excessive image processing of unnecessary information, leading to time consumption and calculation overhead.
Innovation Solution
A method to determine a specific analysis area within the camera image for lane detection, involving the establishment of road and camera coordinate systems, determining the relative relation between them, and converting a defined domain into the analysis area, thereby focusing image processing only on relevant areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all information in the camera image is processed for lane detection, then detection completeness is improved, but processing time and calculation overhead increase
Solution Approach 1:
The patent divides the camera image into multiple regions of interest (ROIs) based on lane detection requirements. By segmenting the image processing task into specific regions (e.g., left lane region, right lane region, center region) rather than processing the entire image, the system maintains detection completeness while significantly reducing the computational burden and processing time.
Solution Approach 2:
The patent applies different processing strategies to different regions of the image. High-precision processing is applied to critical regions where lanes are likely to appear, while lower-precision or skipped processing is applied to regions where lanes are unlikely to appear. This local quality approach ensures that detection reliability is maintained in critical areas while reducing overall processing time.
2Reliability
If all information in the camera image is processed for lane detection, then detection completeness is improved, but calculation overhead increases
Solution Approach 1:
The patent segments the image processing task into multiple region-specific processing streams. Each ROI is processed independently with appropriate algorithms, avoiding the unnecessary calculation of processing the entire image. This segmentation reduces calculation overhead while maintaining detection completeness by ensuring all relevant regions are covered.
Solution Approach 2:
The patent processes only the necessary portions of the image (partial action) rather than the entire image. By identifying and processing only the regions where lanes are likely to appear, the system avoids excessive calculation on irrelevant areas, thereby reducing computational overhead while maintaining sufficient detection completeness.
Data Source
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AI summary
The present invention relates to the fields of intelligent transportation and image processing, and provides a method and device for determining an analysis region for lane detection. The method of the present invention comprises: establishing a road coordinate system; establishing a camera coordinate system; determining a relative position between the road coordinate system and the camera coordinate system, the relative position comprising a lateral offset of a camera with respect to a lane center and an angle between a vehicle direction and a lane direction; determining a first zone in the camera coordinate system, wherein the first zone is required to cover a lane when a lateral offset and angle are achieved; and converting, on the basis of the camera coordinate system, the first zone into an analysis region in a camera image. The present invention achieves theoretical determination of the analysis region to which image processing is applied for lane detection, thereby eliminating computation and processing on unnecessary image regions, and accelerating lane detection.