Vehicle Lens Status Detection Using Image Feature Matching
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Solution Overview
Problem
Current technologies lack effective methods for detecting whether a camera lens on autonomous driving vehicles is dirty, which can lead to incorrect road information and potential safety hazards.
Innovation Solution
A method and apparatus that determine the status of a lens by matching current and historical feature points in images captured by the lens, using algorithms like ORB or SIFT, to identify any distortions or obstructions, and trigger emergency measures if an abnormal status is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature point matching algorithm is used to detect lens status, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the lens detection problem into multiple feature point extraction and matching steps. It divides the image into multiple regions and extracts feature points from each region separately, then matches them systematically. This segmentation approach maintains high detection accuracy while making the computational process more manageable and structured.
Solution Approach 2:
The patent applies partial action by selectively matching feature points based on their reliability and distribution. Instead of matching all extracted feature points equally, it focuses computational resources on high-confidence feature points and regions that provide the most diagnostic information for lens status detection, thereby reducing unnecessary computational complexity.
2Reliability
If real-time lens detection is implemented, then safety response time is improved, but processing speed requirements increase
Solution Approach 1:
The patent performs preliminary action by pre-processing images to enhance feature points before full matching occurs. It also pre-identifies critical regions in the image that are most indicative of lens contamination, preparing these areas for focused analysis. This preliminary preparation enables faster real-time detection while maintaining high reliability.
Solution Approach 2:
The patent applies local quality by differentiating the processing intensity across different image regions. It focuses computational effort on local areas that are most critical for lens status detection (such as regions where contamination is most likely to occur), rather than uniformly processing the entire image. This selective local processing improves both speed and reliability.
Data Source
AI summary
Provided are a method and apparatus for detecting a status of a lens, an electronic device and a medium. A specific implementation includes: determining current feature points included in a current image according to the current image captured at a current moment by a to-be-detected lens of a target driving device; determining historical feature points included in a historical image according to the historical image captured at a historical moment by the to-be-detected lens; and matching the current feature points with the historical feature points and determining a status detection result of the to-be-detected lens according to a matching result. Therefore, an effect of determining a status of the to-be-detected lens of the target driving device is achieved and the problem of a potential safety hazard of the target driving device due to an abnormal status of the to-be-detected lens can be avoided.