Driver Assistance Visibility Determination Using Contrast Sensitivity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance systems using cameras struggle to accurately determine object visibility in a driver's field of view, as they do not account for the human visual system's contrast sensitivity, leading to inconsistencies between detected hazards and their perceptibility by the driver.
Innovation Solution
A method that simulates the human visual system's contrast sensitivity function by applying a series of Gaussian filters to the captured image, allowing for the determination of object visibility without additional sensors, using differences of Gaussians to approximate the contrast sensitivity function and weight filters for accurate representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is used to detect hazards in driver assistance systems, then the system can identify objects in the field of view, but the detection accuracy does not match the actual perceptibility by the driver due to ignoring human visual system characteristics
Solution Approach 1:
The patent creates a computational model (contrast sensitivity function) that copies the characteristics of the human visual system. This model processes the camera image to simulate how the driver's eyes would perceive contrast and visibility, allowing the system to determine which objects are actually visible to the driver without adding physical sensors.
Solution Approach 2:
The patent replaces the need for additional optical sensors with computational image processing. Instead of using complex hardware to directly measure visibility, the system uses software-based contrast sensitivity functions to analyze and interpret the camera data, substituting mechanical sensing with information processing.
2Measurement precision
If additional sensors are added to accurately determine visibility, then the measurement precision improves, but the device complexity and cost increase
Solution Approach 1:
The patent creates a computational model (contrast sensitivity function) that copies the characteristics of the human visual system. This model processes the camera image to simulate how the driver's eyes would perceive contrast and visibility, allowing the system to determine which objects are actually visible to the driver without adding physical sensors.
Solution Approach 2:
The existing camera system performs dual functions: capturing images for basic hazard detection and providing data for visibility analysis through the contrast sensitivity function. The same hardware serves multiple purposes, eliminating the need for dedicated visibility sensors.
3Loss of information
If the camera captures high-resolution images to improve detection, then more detail is available, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the relevant visual information needed for visibility determination by applying contrast sensitivity functions that filter and analyze specific features of the image. Rather than processing all image data equally, the system focuses computational resources on extracting visibility-critical information.
Solution Approach 2:
The contrast sensitivity function applies different processing characteristics to different regions and frequencies of the image, matching the non-uniform sensitivity of the human visual system. This allows efficient processing by focusing computational effort where it is most needed for visibility assessment.
Data Source
Figure 1~3
Figure 4~5
Figure 6~7
AI summary
The invention relates to a method for determining the visibility of objects in a field of view of a driver of a vehicle, in which an image is captured by means of a camera and a contrast sensitivity function (16) describing the human visual system is simulated by image processing of the image captured by the camera. The contrast sensitivity function (16) indicates threshold values of a contrast perceptible by the human visual system in dependency of frequencies. A particular frequency indicates a number of alternations of light and dark areas per angle unit of the field of view. The contrast sensitivity function (16) is approximated by applying a plurality of differences of filters (54, 58, 66) to the image captured by the camera, wherein the differences of filters (54, 58, 66) are each attributed to different frequencies of the contrast sensitivity function (16). Starting from a first frequency of the contrast sensitivity function (16) at least one of further frequencies is determined based on a predetermined relationship between the first frequency and the further frequencies of the contrast sensitivity function. The respective differences of filters (54, 58, 66) are assigned to the frequencies. In dependence on the differences of filters (54, 58, 66) the visibility of an object in the field of view of the driver is determined. The invention further relates to a driver assistance system and a motor vehicle with a driver assistance system,