ADAS Image Pre-processing via Skyline Detection
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Solution Overview
Problem
Current advanced driver-assistance systems (ADAS) in vehicles process full image frames, including irrelevant sky portions, leading to increased energy consumption and latency due to unnecessary data transmission and processing.
Innovation Solution
Implementing image pre-processing techniques to identify and crop out the skyline portion from image frames, allowing only relevant data to be transmitted and processed, reducing the load on the vehicle's data bus and improving processing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If full image frames are transmitted to ADAS ECUs, then complete image data is available for processing, but data transmission size increases and bandwidth is reduced
Solution Approach 1:
The patent extracts and removes the skyline portion (sky region) from image frames before transmission to ADAS ECUs. By identifying the skyline horizon and cropping out the region above it, the system transmits only the relevant ground portion containing potential objects of interest, thereby reducing data transmission size while preserving all necessary information for ADAS functionality.
Solution Approach 2:
The patent segments the image frame into two distinct portions: the skyline portion (sky region above the horizon) and the ground portion (region below the horizon containing relevant objects). By separating these segments and transmitting only the ground portion, the system reduces overall data transmission while maintaining completeness of relevant information for ADAS processing.
2Reliability
If full image frames are processed by ADAS ECUs, then all potential objects are detected, but processing time increases causing latency
Solution Approach 1:
The patent extracts and removes the skyline portion from image frames before transmission to ADAS ECUs. By identifying the skyline horizon and cropping out the region above it, the system transmits only the relevant ground portion containing potential objects of interest, thereby reducing data transmission size while preserving all necessary information for ADAS functionality.
Solution Approach 2:
The patent performs preliminary cropping of image frames to remove the skyline portion before transmission to ADAS ECUs. This pre-processing action eliminates unnecessary data in advance, so that when ADAS ECUs receive the cropped images, they can process them faster without the overhead of analyzing irrelevant sky regions, thereby reducing processing latency.
3Loss of information
If full image frames are transmitted over the vehicle data bus, then all image data reaches the ADAS ECUs, but energy consumption increases
Solution Approach 1:
The patent extracts and removes the skyline portion from image frames before transmission to ADAS ECUs. By identifying the skyline horizon and cropping out the region above it, the system transmits only the relevant ground portion containing potential objects of interest, thereby reducing data transmission size while preserving all necessary information for ADAS functionality.
Solution Approach 2:
The patent performs preliminary cropping of image frames to remove the skyline portion before transmission to ADAS ECUs. This pre-processing action eliminates unnecessary data in advance, so that when ADAS ECUs receive the cropped images, they can process them faster without the overhead of analyzing irrelevant sky regions, thereby reducing processing latency.
4Quantity of substance
If skyline detection and cropping is implemented, then data transmission size is reduced, but system complexity increases
Solution Approach 1:
The patent implements self-service by having the camera module perform its own skyline detection and cropping operations autonomously without requiring external assistance from ADAS ECUs. The camera identifies the skyline horizon and crops the image frame independently, then transmits only the cropped ground portion to the ADAS ECU, thereby reducing data transmission size while maintaining relatively simple system architecture.
Data Source
AI summary
Disclosed are techniques for improving an advanced driver-assistance system (ADAS) by pre-processing image data. In one embodiment, a method is disclosed comprising receiving one or more image frames captured by an image sensor installed on a vehicle; identifying a position of a skyline in the one or more image frames, the position comprising a horizontal position of the skyline; cropping one or more future image frames based on the position of the skyline, the cropping generating cropped images comprising a subset of the corresponding future image frames; and processing the cropped images at an advanced driver-assistance system (ADAS).