Camera Lens Contaminant Detection for Autonomous Driving Vision
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Solution Overview
Problem
Existing camera systems for autonomous vehicles lack the capability to automatically detect and recognize contaminants on the camera lens, leading to degraded recognition performance and requiring manual intervention.
Innovation Solution
A method and system for automatically recognizing contaminants on a camera lens by receiving an image, pre-processing it, and using semantic segmentation to identify opaque, translucent, and normal regions, followed by accumulation and extraction of contaminants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual cleaning method is used, then user can clean the lens, but automatic recognition function is not provided and recognition performance degrades without user awareness
Solution Approach 1:
The camera system performs self-diagnosis by automatically detecting contaminants on its own lens using image processing algorithms. The system captures images through the camera lens, processes them to identify contamination regions, and generates alerts without requiring external intervention or additional specialized sensors, enabling the system to monitor and report its own operational status.
2Reliability
If no automatic detection is implemented, then system complexity remains low, but recognition performance degrades and manual intervention is required
Solution Approach 1:
The existing camera used for capturing road scenes is made multi-functional by adding image processing capabilities that enable contaminant detection. The same imaging hardware serves dual purposes: normal scene capture and self-diagnosis for contaminant detection, eliminating the need for separate specialized detection devices and maintaining system simplicity while improving reliability.
Solution Approach 2:
The patent replaces complex mechanical or specialized optical detection systems with software-based image processing algorithms. By using computational methods to analyze images captured by the existing camera, the system achieves reliable contaminant detection without requiring additional mechanical sensors or complex hardware modifications.
3Reliability
If continuous monitoring is implemented, then recognition performance is maintained, but energy consumption increases
Solution Approach 1:
Instead of continuous real-time analysis, the system performs contaminant detection at periodic intervals or triggered by specific conditions. The image processing is executed periodically or when contamination is suspected, reducing computational load and energy consumption while maintaining adequate monitoring effectiveness for autonomous driving operations.
Data Source
AI summary
Provided are a method and a system for detecting contaminants attached to a camera lens. A camera contaminant detection method according to an embodiment includes: receiving an image through a camera; pre-processing the inputted image; and identifying a contamination region to which contaminants are attached and a normal region to which contaminants are not attached in the pre-processed image. Accordingly, by automatically detecting whether contaminants are attached to a camera for autonomous driving and the location of attachment, auto-cleaning or contamination alarms may be performed to prevent degradation of recognition performance caused by contaminants on the camera for autonomous driving.