Image Processor Coordinate Deviation Correction Timing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing stereo camera systems face challenges in accurately measuring distances due to minute deformations caused by temporal changes and temperature fluctuations, leading to false obstacle recognition in vehicle control systems, particularly when updating correction coefficients coincides with image usage timing.
Innovation Solution
An image processor that includes a corrector to adjust image coordinates using a stored correction parameter and an updater to generate and update this parameter based on processed images, ensuring timely correction and minimizing false recognition by controlling the updating process according to vehicle control system conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the correction parameter is updated frequently to maintain accuracy, then measurement precision improves, but false recognition increases when updates coincide with image usage timing
Solution Approach 1:
The system performs preliminary validation by checking whether the photographed image is being used for obstacle recognition or tracking before updating the correction parameter. This advance check prevents updates from occurring at critical moments when images are being processed for safety-critical functions, thereby avoiding false obstacle recognition while maintaining measurement accuracy through timely updates.
2Device complexity
If the correction parameter is updated at fixed intervals, then device complexity is reduced, but measurement precision deteriorates due to temporal changes and temperature fluctuations
Solution Approach 1:
The system transitions from fixed-interval updates to dynamic, condition-based updates. The update timing adapts to actual system conditions by monitoring whether obstacle recognition or tracking is in progress, allowing the correction parameter to be updated at optimal moments that account for temporal changes and temperature fluctuations without requiring complex scheduling mechanisms.
3Reliability
If obstacle recognition and tracking processes are continuously running, then reliability improves, but productivity decreases due to computational overhead
Solution Approach 1:
The system extracts and isolates the critical safety function (obstacle recognition and tracking) from the general image processing flow. By checking specifically for the presence of these processes before updating correction parameters, the system ensures reliable obstacle detection while allowing other image processing operations to proceed without unnecessary computational overhead, thus maintaining productivity.
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
An image processor (11) includes a corrector (106) that corrects deviation of a coordinate in an image photographed by a photographing unit based on a correction parameter stored in a memory; and an updater (104) that generates the correction parameter based on the image photographed by the photographing unit, and updates the correction parameter stored in the memory, the updater updating the correction parameter according to a process condition based on the image corrected by the corrector.