Adaptive Image Aim Calibration for Vehicle Vision Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle vision systems face challenges in accurately aligning cameras due to manufacturing variations and changing road conditions, leading to potential misclassification of light sources and inadequate glare control, which can result in driver dissatisfaction.
Innovation Solution
The system employs adaptive image aim calibration that occurs with every image cycle, using lane markers and illumination gradients to quickly determine the road center and classify bright peaks, thereby improving the accuracy of light source identification and reducing the need for factory aim calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If factory aim calibration is performed, then initial camera alignment is improved, but the system cannot adapt to manufacturing variations and changing road conditions
Solution Approach 1:
The patent implements dynamic aim calibration that continuously adapts to changing conditions by processing live video feeds and adjusting camera parameters in real-time, transforming the static factory calibration into a dynamic self-correcting system that maintains accuracy despite manufacturing variations and environmental changes
Solution Approach 2:
The system performs self-calibration by automatically detecting road features and light sources in the environment, using these natural references to correct its own alignment without requiring external intervention or recalibration equipment, thereby adapting to both manufacturing variations and changing road conditions
2Measurement precision
If adaptive image aim calibration is performed with every image cycle, then light source classification accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system applies partial calibration actions by focusing computational resources only on critical image cycles or specific regions of interest within the image, performing full adaptive calibration selectively rather than on every single image frame, thereby maintaining accuracy while reducing overall processing time
Solution Approach 2:
The patent implements periodic calibration cycles where full adaptive aim calibration is performed at intervals rather than continuously on every image, allowing the system to maintain accuracy through regular updates while reducing computational load during intermediate periods
Data Source
AI summary
An image acquisition and processing system includes an image sensor and one or more processors that are configured to receive at least a portion of at least one image from the image sensor. The dynamic aim of the image sensor is configured as a function of at least one feature extracted from at least a portion of an image. To accomplish the task, the system utilizes a series of adaptive thresholds used in parallel comparators to determine whether or not a pixel in a given image scene falls on the edge of a given lane line on a road. The location of the lane lines are then used to determine the scene vanishing point, which ideally will be co-located at the optical scene center. If they are not in agreement, the pixel data set being processed can be adjusted to accommodate for any disagreement.