Vehicle Camera Misalignment Detection via Pre-Post Drive Image Comparison
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Solution Overview
Problem
Dashboard cameras on vehicles may become misaligned during cleaning, leading to unintended image capture directions when driving resumes, resulting in inadequate recording.
Innovation Solution
An information processor acquires and compares pre-driving and post-driving images from the vehicle's camera to detect misalignment, using regions of the vehicle for accurate comparison and issuing warnings or corrections as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the imaging device is left unattended during vehicle cleaning, then the cleaning process can be completed efficiently, but the camera may become misaligned leading to incorrect image capture direction
Solution Approach 1:
The system performs preliminary alignment detection by capturing an image before driving starts and comparing it with a reference image captured after driving finishes. This preliminary check allows detection of misalignment caused during cleaning, enabling correction before actual driving begins, thus resolving the contradiction between cleaning efficiency and camera alignment precision
Solution Approach 2:
The system implements feedback by detecting misalignment through image comparison and providing notifications to the user. The detection section compares the pre-driving image with the reference image, and when misalignment is detected, it triggers a notification to alert the driver, creating a feedback loop that ensures camera alignment is verified and corrected if necessary
2Measurement precision
If image comparison is performed on the entire image area, then comprehensive alignment checking is achieved, but false detection may occur due to background changes
Solution Approach 1:
The system divides the image into multiple regions and performs alignment detection on specific regions containing vehicle parts rather than the entire image. By segmenting the image and focusing on regions with stable vehicle features, the system achieves reliable alignment detection without false positives from background changes, resolving the contradiction between measurement precision and detection reliability
3Manufacturing precision
If misalignment detection is performed continuously, then alignment accuracy is maintained, but energy consumption and processing time increase
Solution Approach 1:
The system performs misalignment detection periodically at specific moments - when driving starts and when driving finishes - rather than continuously. This periodic action captures the critical transition points where misalignment is most likely to occur (during cleaning between drives), maintaining alignment precision while minimizing processing time and energy consumption
Data Source
AI summary
The disclosure includes: a first acquisition section that acquires a first image captured by an imaging device mounted on a vehicle after driving of the vehicle is finished; a second acquisition section that acquires a second image captured by the imaging device when driving of the vehicle is started; and a detection section that detects misalignment between the first image and the second image.