Vehicle Image Processing for Lane Line Type and Instance Determination
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Solution Overview
Problem
Existing vehicle control systems struggle to accurately determine the type and instance of lane lines from images captured by vehicle-mounted cameras, which is crucial for safe and efficient vehicle operation.
Innovation Solution
An image processing method that involves receiving an original image from a vehicle-mounted camera, generating detail feature information through multiple processing schemes, determining the type and instance of target lines by processing contextual information, and using a neural network-based model to control the vehicle accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple processing schemes are used to generate detail feature information and contextual information, then the precision of determining lane line type and instance is improved, but the complexity of the image processing system increases
Solution Approach 1:
The patent applies segmentation by dividing the image processing into multiple independent processing schemes: first detail feature information extraction, second detail feature information extraction, lane type contextual information extraction, and lane instance contextual information extraction. Each scheme processes different aspects of the image independently, then the results are integrated to achieve precise lane line type and instance determination while maintaining modular system architecture.
2Measurement precision
If detailed feature information is generated through multiple processing schemes, then the accuracy of lane line identification is improved, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-extracting and organizing different types of feature information (first detail features, second detail features, lane type context, lane instance context) through separate processing schemes before the actual lane line identification. This preprocessing approach allows the system to quickly retrieve and integrate pre-computed features during real-time operation, improving identification accuracy while reducing real-time processing time.
Data Source
AI summary
In order to process an image according an embodiment: first detailed feature information may be generated by processing an original image; second detailed feature information may be generated by processing the first detailed feature information; lane type context information may be generated by processing the original image; a type of a target lane in the original image may be determined on the basis of the second detailed feature information and the lane type context information; lane instance context information may be generated by processing the first detailed feature information; and an instance of the target lane may be determined on the basis of the second detailed feature information and the lane instance context information.