Vehicle Rearview Image Stabilization via Horizon Detection
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Solution Overview
Problem
Current display systems for vehicles fail to automatically adjust the rearview image to compensate for changes in vehicle orientation and road conditions, leading to unstable and suboptimal image display.
Innovation Solution
A display system comprising an imager and a controller that captures and processes image data to identify features like the horizon and vanishing point, adjusting the image position and orientation in real-time to maintain a stable and optimal view on the display screen, incorporating user preferences and adaptive edge detection algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If automatic image adjustment is implemented to compensate for vehicle orientation changes, then image stability is improved, but device complexity increases
Solution Approach 1:
The system performs self-adjustment by automatically detecting features (horizon, vanishing point, road markings) in the captured image and computing the necessary transformation parameters. The controller autonomously determines the vehicle's orientation state and applies corrective transformations without requiring manual intervention, thereby improving image stability while avoiding the complexity of manual adjustment mechanisms.
Solution Approach 2:
The system continuously captures images, detects features, compares the detected feature positions with expected positions, and adjusts the image transformation parameters accordingly. This closed-loop feedback mechanism ensures that the image remains stable despite vehicle orientation changes, resolving the contradiction between image stability and device complexity by using intelligent algorithms rather than complex hardware.
2Adaptability or versatility
If real-time image processing is performed to adjust for road conditions, then adaptability is improved, but use of energy increases
Solution Approach 1:
The system processes only the necessary portions of the image data required for feature detection and transformation. Rather than analyzing every pixel in the entire image, the system focuses computational resources on detecting key features (horizon line, vanishing point, road markings) and computing the essential transformation parameters, thereby reducing energy consumption while maintaining adaptability to road conditions.
3Device complexity
If manual adjustment of rearview image is required, then device complexity is reduced, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects the vehicle's orientation state by analyzing features in the captured image and performs self-adjustment by applying the appropriate transformation. This eliminates the need for manual adjustment mechanisms and operations, providing a simple, automatic solution that improves ease of operation without significantly increasing device complexity, as the adjustment logic is handled by software algorithms.
Data Source
AI summary
A display system for a vehicle comprises an imager configured to capture image data in a field of view rearward relative the vehicle. The system further comprises a display device and a controller. The display device comprises a screen disposed in a passenger compartment of the vehicle. The controller is in communication with the imager and the display device. The controller is operable to process the image data to identify at least one feature. Based on a position or orientation of the at least one feature in the image data, the controller adjusts at least one of a position and an orientation of a desired view of the image data for display on the screen.