Vehicular Vision System Image Manipulation for Hazard Visibility
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Solution Overview
Problem
Vehicle camera systems struggle to provide video that is quickly and reliably comprehensible to drivers, especially in situations requiring attention to hazards around the vehicle, due to distortion caused by wide-angle lenses.
Innovation Solution
A vehicle vision system that uses a single camera with a wide-angle lens, coupled with a processor, to manipulate image data by applying different image manipulation techniques to distinct regions of the captured image, such as dewarping and reshaping, to enhance the visibility of hazards and provide a continuous field of view on a display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide-angle lens is used to capture a broad field of view, then the coverage area is improved, but image distortion increases making hazards difficult to identify
Solution Approach 1:
The image is divided into multiple regions (first region, second region, third region) with different manipulation techniques applied to each. The central region uses dewarping to correct distortion, while side regions use reshaping to expand the field of view, resolving the contradiction between coverage and distortion.
Solution Approach 2:
Different regions of the image receive different quality treatments. The central region undergoes dewarping for accurate hazard identification, while peripheral regions undergo reshaping for expanded coverage, allowing each region to have optimal quality for its specific purpose.
2Loss of information
If image manipulation techniques are applied to correct distortion, then image comprehensibility is improved, but processing complexity increases
Solution Approach 1:
The processing is segmented into distinct operations for different regions. The processor applies dewarping to the central region and reshaping to side regions independently, making the complex processing task more manageable and efficient.
Solution Approach 2:
The system performs preliminary image manipulation by dividing the image into regions and applying appropriate transformations before display. This preliminary processing ensures comprehensibility is achieved while organizing the complexity into structured, manageable steps.
3Measurement precision
If multiple image manipulation techniques are applied to different regions, then hazard visibility is improved, but computational resources increase
Solution Approach 1:
Computational resources are segmented and allocated to different regions based on their specific needs. The central region receives dewarping processing for hazard accuracy, while peripheral regions receive reshaping for coverage, optimizing energy usage by not applying all processing techniques to all regions.
Solution Approach 2:
Computational energy is distributed locally based on region requirements. High-precision dewarping is applied only where hazard identification is critical (central region), while peripheral regions receive less computationally intensive reshaping, balancing accuracy with energy consumption.
Data Source
AI summary
A vehicular vision system includes a camera disposed at a front portion of a vehicle, a display screen and a processor for processing image data captured by the camera. The processor performs first, second and third image manipulations on first, second and third portions of the image data to generate first, second and third region manipulated image data. The display screen displays first, second and third images derived from the manipulated image data at respective display regions. The displayed images are discontinuous at a first seam between first and second display regions and discontinuous at a second seam between first and third display regions. An object present in first and second regions of the view of the camera is displayed as discontinuous at the first seam and an object present in the first and third regions of the view of the camera is displayed as discontinuous at the second seam.