Windshield Droplet Detection Using Vehicle Camera Binary Imaging
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Solution Overview
Problem
Existing vehicle systems lack an efficient method to detect droplet presence on windshields, particularly in conditions where conventional rain sensors are ineffective, leading to suboptimal wiper control during rainfall or snowfall.
Innovation Solution
A system utilizing vehicle cameras to capture images, convert them into binary images using AI/ML algorithms, and control wiper movement based on droplet presence and count, potentially augmented by inputs from additional cameras and sensors, eliminating the need for conventional rain sensing modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional rain sensors are used to detect droplet presence, then the system can control wiper movement, but the detection accuracy deteriorates in certain weather conditions
Solution Approach 1:
The patent replaces conventional rain sensors with a camera-based vision system that uses image processing and machine learning algorithms to detect droplets. The camera captures images of the windshield, and AI algorithms analyze the images to identify droplet patterns, replacing the mechanical/electrical sensing approach with an optical-computational approach that provides better detection accuracy across various weather conditions.
Solution Approach 2:
The system changes the detection parameter from electrical signals (conventional sensors) to visual image data. By capturing images and analyzing pixel patterns, color variations, and droplet shapes through machine learning, the system adapts to different weather conditions by processing visual information rather than relying on fixed electrical sensing thresholds.
2Measurement precision
If AI/ML algorithms are used to analyze images for droplet detection, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent leverages the vehicle's existing camera system, which is already part of the vehicle's standard equipment for other purposes. By making the camera multi-functional (serving both its original purpose and droplet detection), the system achieves high detection precision without adding significant complexity. The same hardware is reused for multiple functions, reducing the net increase in system complexity.
Solution Approach 2:
The system uses the vehicle's existing computational resources and processing units to run the AI/ML algorithms. Rather than requiring dedicated specialized hardware, the patent utilizes the vehicle's onboard computer and existing processing capabilities to perform the image analysis, thereby reducing the need for additional complex hardware components.
Data Source
AI summary
A vehicle having a windshield and a camera is disclosed. The camera may be configured to capture a first image of a vehicle surrounding area through the windshield. The vehicle may further include an image processing module configured to determine a plurality of gradients associated with a plurality of pixels in the first image and an unfocused object present in the first image based on the plurality of gradients. The image processing module may be further configured to generate a binary image using the first image responsive to determining the unfocused object. The vehicle may further include a processor configured to determine a droplet presence on the windshield based on the binary image and perform a predefined action responsive to determining droplet presence on the windshield.