Polarimetric Camera Road Marking Detection Glare Removal
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Solution Overview
Problem
Vehicle sensors, particularly camera sensors, face challenges in detecting road features like lane markings on wet or icy roads due to environmental conditions, leading to impaired accuracy in vehicle operation.
Innovation Solution
A processing system that utilizes polarimetric camera sensors to identify polarized light reflections from road surfaces, removes these reflections, and generates an updated image to enhance road feature detection, allowing for improved lane marking recognition and vehicle actuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a camera sensor is used to detect road markings, then the vehicle can operate with basic sensor equipment, but the sensor cannot detect markings on wet roads due to polarized light reflections
Solution Approach 1:
The patent converts the harmful polarized light reflections into a useful signal by detecting their polarization characteristics. The system identifies regions with high polarization degrees as reflections and selectively processes these areas to remove the glare effect, thereby improving road marking detection on wet surfaces.
Solution Approach 2:
The patent changes the parameter of light detection by incorporating polarization degree measurement. Instead of only detecting light intensity, the system measures the polarization state of reflected light to distinguish between useful road marking information and harmful reflections, enabling effective filtering of glare artifacts.
2Measurement precision
If polarimetric camera sensors are used to detect polarized light reflections, then road feature detection accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent segments the image processing into distinct functional modules: polarization degree calculation, reflection region identification, and selective artifact removal. This modular approach allows the complex polarimetric processing to be broken down into manageable steps that can be implemented efficiently in existing camera systems.
Solution Approach 2:
The patent applies polarimetric processing selectively only to regions identified as containing polarized reflections, rather than processing the entire image with full polarimetric analysis. This partial action approach reduces computational complexity while maintaining measurement precision in the critical affected areas.
3Measurement precision
If polarized light reflections are removed from the image, then lane marking recognition accuracy is improved, but information about the road surface condition may be lost
Solution Approach 1:
The patent extracts only the harmful polarized reflection components from the image while preserving the underlying road marking information. By identifying and removing specifically the polarized glare artifacts rather than entire image regions, the system maintains road surface condition data while eliminating detection interference.
Solution Approach 2:
The patent uses polarization degree mapping as an intermediary to bridge the conflict between removing reflections and preserving information. The polarization degree map serves as a guide to selectively process only the reflective artifacts, allowing the system to remove harmful elements while maintaining useful road surface information for other processing functions.
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
The system effectively improves road feature detection on wet or icy surfaces by ignoring polarized light reflections, enabling more accurate lane marking recognition and maintaining vehicle stability.
Implementation Method 1
identify polarized light reflections from the road surface based on a polarization direction and a polarization degree determined from the polarimetric image
Data Source
AI summary
A processing system comprises a processor and a memory. The memory stores instructions executable by the processor to receive a polarimetric image from a polarimetric camera sensor, and to identify a road surface in the received image based on a vehicle location, an orientation of the camera sensor, and a vehicle pose. The memory stores instructions, upon identifying, in the polarimetric image, polarized light reflections from the identified road surface based on a polarization direction and a polarization degree determined from the polarimetric image, to remove the identified polarized light reflections from the polarimetric image, thereby generating an updated polarimetric image including generating a de-mosaicked imaged based on the identified polarized light reflections, wherein the identified polarized light reflections are ignored at de-mosaicking, and to identify a road feature including a lane marking based on the updated polarimetric image.