Dynamic Image Region Setting for Vehicle Periphery Recognition
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Solution Overview
Problem
Existing vehicle periphery recognition systems fail to consider various factors when determining the image region for analysis, leading to suboptimal performance during actual driving conditions.
Innovation Solution
An image processing apparatus that uses GPS data, vehicle information, and road information to dynamically set the image region for analysis based on travel speed, steering angle, and lighting conditions, allowing for adaptive extraction of peripheral images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed size and direction image is captured for analysis, then the analysis process is simple, but the recognition accuracy during actual driving deteriorates because the image region does not adapt to changing vehicle conditions
Solution Approach 1:
The patent applies dynamics by making the image capture region and analysis region variable rather than fixed. The control unit dynamically adjusts the capture region based on vehicle speed, steering angle, and other movement information. Additionally, the analysis region is dynamically determined based on the captured image content, allowing the system to adapt to changing driving conditions and maintain high recognition accuracy without excessive complexity.
Solution Approach 2:
The patent changes parameters by adjusting the size, position, and shape of the capture region based on vehicle movement parameters (speed, steering angle, tilt angle). The analysis region parameters are also changed based on the captured image content. This parameter adaptation allows the system to optimize recognition accuracy for different driving scenarios while managing processing complexity through selective parameter adjustment.
2Reliability
If the entire peripheral image is processed, then complete coverage is achieved, but processing time and computational load increase significantly
Solution Approach 1:
The patent extracts only the necessary portion of the peripheral image for analysis by defining a specific analysis region within the captured image. The control unit determines this analysis region based on the captured image content and vehicle conditions, extracting only the relevant area for processing. This extraction approach maintains detection completeness for important elements while significantly reducing processing time and computational load by avoiding unnecessary processing of the entire image.
Solution Approach 2:
The patent applies partial action by processing only a portion of the captured image rather than the entire image. The analysis region is set to cover only the necessary area based on vehicle conditions and image content, implementing partial processing that maintains adequate detection capability while reducing overall processing time and computational resources required.
3Measurement precision
If the image capture region is adjusted based on vehicle movement information, then recognition accuracy improves, but the determination process becomes more complex
Solution Approach 1:
The patent applies preliminary action by pre-establishing the relationship between vehicle movement information (speed, steering angle, tilt angle) and the appropriate capture region settings. The control unit uses predetermined rules and algorithms to quickly determine the capture region based on current vehicle state, avoiding complex real-time calculations. This preliminary preparation maintains high image region accuracy while keeping the determination process relatively simple and efficient.
Data Source
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AI summary
An image processing apparatus 14 includes a road information receiver 24 and a region setter 25. The road information receiver 24 obtains road information around a movable object. The region setter 25, based on the road information, sets a region of a peripheral image of the movable object to extract.