Lane Departure Warning System Temporal Validation
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Solution Overview
Problem
Conventional lane-detection algorithms for lane departure warning systems are prone to noise sensitivity and high computational complexity, and require complex hardware implementations, which affect their reliability and efficiency.
Innovation Solution
A method and system that validate candidate regions for lane markers by determining the minimum distance between new and previously verified regions, storing them as verified or rejected based on a threshold, and refining vanishing point estimates through statistical averaging, using an image processor and memory to execute these processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional lane-detection algorithms use feature detection schemes, then lane marker detection can be performed, but noise sensitivity increases and measurement precision deteriorates
Solution Approach 1:
The patent applies preliminary action by using temporal sequence analysis and historical lane marker positions to predict and validate candidate regions before final detection. The system prepares reference data from previous frames and uses it to pre-filter potential lane markers, reducing noise sensitivity while maintaining precision through proactive validation rather than reactive correction.
2Reliability
If conventional lane-detection algorithms use complex feature detection schemes, then detection capability is improved, but computational complexity increases and productivity decreases
Solution Approach 1:
The patent applies partial action by focusing computational resources only on candidate regions that meet preliminary criteria rather than processing the entire image with full feature detection. The system performs simplified detection on selected regions and uses temporal consistency checks to validate results, achieving high detection capability with reduced computational overhead and improved processing speed.
3Measurement precision
If conventional lane-detection algorithms use detailed feature detection, then detection accuracy is improved, but device complexity increases and ease of manufacture deteriorates
Solution Approach 1:
The patent applies mechanics substitution by replacing complex hardware-based feature detection mechanisms with software-based temporal sequence analysis and statistical validation. The system uses image processing algorithms that leverage time-series data and probability models to achieve high detection accuracy without requiring complex hardware implementations, thereby simplifying the overall device architecture.
Data Source
AI summary
A lane departure warning system includes a memory and a processor for validating a candidate region as including an image of a lane marker on the road is disclosed. The candidate region is identified within a latest road image of a temporal sequence of road images captured from the front of a vehicle traveling along a road. The memory stores non-transitory computer-readable instructions and adapted to store the road image. The image processor is adapted to execute the instructions to, when no previously-verified region and no previously-rejected region aligns with the candidate region: (i) determine a minimum distance between the candidate region and a previously-verified region of a previously-captured road image of the sequence, (ii) when the minimum distance exceeds a threshold distance, store the candidate region as a verified region, and (iii) when the minimum distance is less than the threshold distance, store the candidate region as a rejected region.