Vehicle Fog Detection via Obstacle Masking and Luminance Analysis
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Solution Overview
Problem
Existing methods for determining the presence of fog around a vehicle using vehicle-mounted cameras are inaccurate due to the need for identifying sky areas, reliance on multiple cameras for moving vehicles, and difficulty in dense fog conditions, as well as interference from obstacles like preceding vehicles and high-luminance objects.
Innovation Solution
An apparatus and method that captures images ahead of a vehicle, extracts a reference image, detects high-luminance obstacles, masks their areas, and calculates total luminance intensity to determine fog presence, reducing errors by focusing on scattered light from the sun and improving reliability through masking and spatial frequency analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fog detection methods are used, then the system can operate with simple equipment, but the detection accuracy deteriorates due to interference from obstacles and high-luminance objects
Solution Approach 1:
The patent extracts and removes the influence of obstacles and high-luminance objects from the image analysis process. By identifying regions containing these interfering objects and excluding them from the fog detection calculation, the system achieves accurate fog detection without requiring complex hardware modifications, thus resolving the contradiction between detection accuracy and device complexity.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image. Regions containing obstacles or high-luminance objects are treated differently (masked or excluded) compared to regions used for fog detection. This localized differentiation allows accurate fog detection in the presence of interfering objects without requiring the entire system to be overly complex.
2Adaptability or versatility
If multiple cameras are used to capture images from different positions, then the system can handle moving vehicles better, but the device complexity and cost increase
Solution Approach 1:
The patent segments the image into different regions (e.g., sky region, obstacle region, foreground region) and processes each region according to its specific characteristics. By segmenting the image data rather than using multiple cameras, the system achieves adaptability to moving vehicles while avoiding the complexity of multiple camera systems.
3Reliability
If the system processes the entire image for fog detection, then the measurement coverage is complete, but the detection reliability deteriorates due to noise from obstacles
Solution Approach 1:
The patent extracts and removes obstacle regions from the image processing area. By identifying and excluding regions containing obstacles, the system maintains reliable fog detection based on the remaining valid image areas, resolving the contradiction between complete coverage and detection reliability.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image. Regions containing obstacles or high-luminance objects are treated differently (masked or excluded) compared to regions used for fog detection. This localized differentiation allows accurate fog detection in the presence of interfering objects without requiring the entire system to be overly complex.
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 method enhances the accuracy of fog detection by reducing noise from obstacles and improving reliability, allowing for precise determination of fog presence even in dense conditions, thereby enhancing driver safety.
Implementation Method 1
In fog, a proportion of the light is scattered by water droplet. Because the absorption of visible light by water droplets can be negligible, the scattering and extinction coefficient are considered to be interchangeable.
Implementation Method 2
The fog effects on the atmospheric visibility are modeled by Koschmieder's law on the apparent luminance of observed objects against background sky on the horizon. This expression indicates that the luminance of the object observed through fog is attenuated as e−kd, and a luminance reinforced by daylight scattered from the atmospheric particles between the object and the observer has a form of L∞(1−e−kd).
Data Source
AI summary
An apparatus that determines the presence of an element such as fog interfering with the visibility of a frontal view of an driver in an vehicle in an environmental atmosphere in ahead of the vehicle equipped with the apparatus in the daytime is provided. In this apparatus, the determination of whether the presence of the element is determined based on an image that captured by a vehicle-mounted camera and in which a picture of an obstacle located on a road over which the vehicle is traveling is masked. In the determination, a reliability of determining the presence of the element is considered by measuring the effect of masking the obstacle.