Image Sensor Region Parameter Control for Automotive Safety
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional forward-looking automobile camera systems face challenges in cost-effectiveness due to vibration, shock, and limited capability to control sensor parameters, resulting in poor resolution that hinders their use in supporting comprehensive safety applications.
Innovation Solution
An image sensor system with independently adjustable parameters such as resolution, exposure time, and gain in multiple regions of interest, allowing for tailored settings based on specific detection tasks, reducing the need for full high-resolution mode operation and enhancing image recognition reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional forward-looking automobile camera systems use a single global sensor parameter setting for the entire image, then device complexity is reduced and ease of operation is improved, but measurement precision and image quality in specific regions of interest deteriorate
Solution Approach 1:
The image sensor is divided into multiple independently controllable regions of interest (ROIs), each capable of having its own sensor parameters (exposure time, gain, resolution) set independently. This segmentation allows precise optimization for different detection tasks in different spatial regions without requiring complex global control mechanisms.
Solution Approach 2:
Different regions of the image sensor are assigned different quality characteristics and parameter settings based on their specific detection requirements. For example, regions detecting pedestrians may use higher gain and exposure settings, while regions detecting distant vehicles use different settings, optimizing local image quality for each function.
2Measurement precision
If the image sensor operates in full high-resolution mode across the entire sensor array, then measurement precision is improved, but use of energy increases and productivity decreases due to unnecessary data processing
Solution Approach 1:
Instead of operating the entire sensor array at full resolution, the system applies high-resolution settings only to specific regions of interest where detection precision is critical. Other regions operate at lower resolution or are excluded from processing, reducing overall power consumption and data processing requirements while maintaining sufficient precision for safety applications.
3Reliability
If conventional systems use radar-based collision avoidance systems to improve measurement precision and reliability, then detection accuracy is improved, but device complexity and cost increase significantly
Solution Approach 1:
The image sensor system is designed to perform multiple detection functions (pedestrian detection, vehicle detection, obstacle detection) simultaneously by configuring different regions for different tasks. This multi-functionality replaces the need for separate radar systems while achieving comparable reliability through intelligent parameter control and image processing.
4Adaptability or versatility
If the image sensor adjusts parameters for the entire image based on a single region of interest analysis, then adaptability is improved, but measurement precision in other regions deteriorates due to suboptimal parameter settings
Solution Approach 1:
The sensor is segmented into multiple independently controllable regions, each with its own parameter adjustment capability. This allows each region to be independently optimized for its specific detection task while maintaining overall system adaptability to different driving conditions and scenarios.
Data Source
AI summary
An image sensing systems supports independently setting sensor parameters in two or more different regions of interest. In one implementation resolution, exposure time, and gain are independently selectable in each region of interest. Independently setting exposure time and gain in different regions of interest improves image recognition when there are large differences in the illumination of objects within an image. Independently setting resolution permits the resolution to be selectively increased in regions of interest requiring high resolution in order to reduce the pixel data bandwidth and processing requirements.