Lane Line Detection Using Optical Flow Search Regions
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Solution Overview
Problem
Existing lane line detection technologies face significant computation burdens, which can lead to slow detection speeds, compromising the ability to rapidly identify lane lines and prevent accidents.
Innovation Solution
A method utilizing a dynamic vision sensor to generate an optical flow image, determining initial and subsequent search regions based on the optical flow, and iteratively calculating centers of gravity to detect lane lines without edge detection, thereby reducing computational load and improving detection speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If edge detection and curve fitting methods are used for lane line detection, then detection accuracy is improved, but computation burden increases and detection speed decreases
Solution Approach 1:
The patent segments the image processing task by dividing it into multiple search regions rather than processing the entire image. Each search region is processed independently to detect lane lines, which reduces the overall computational burden while maintaining detection accuracy through focused local analysis.
Solution Approach 2:
The patent extracts only the necessary features (optical flow information and center of gravity) from the image data, ignoring unnecessary details. This selective extraction approach reduces computation by focusing only on relevant characteristics needed for lane line detection.
2Loss of information
If traditional edge detection methods are applied to extract lane line information, then comprehensive lane line features are obtained, but computation resources are heavily consumed
Solution Approach 1:
The patent extracts only the essential optical flow information and center of gravity characteristics from the image, discarding unnecessary edge detection computations. This selective feature extraction maintains sufficient lane line detection capability while significantly reducing computation resource consumption.
Solution Approach 2:
The patent uses optical flow information as a simplified representation or 'copy' of the full image data, which contains the necessary motion and lane line information without requiring processing of the complete original image, thus reducing computational requirements.
Data Source
AI summary
The present disclosure provides a method for detecting a lane line, a vehicle and a computing device. The method includes: generating an optical flow image in accordance with a series of event data from a dynamic vision sensor coupled to a vehicle; determining an initial search region including a start point of the lane line in accordance with the optical flow image; determining a center of gravity of the initial search region; determining a new search region through an offsetting operation on the center of gravity; determining a center of gravity of the new search region; repeating the steps of determining a new search region and determining a center of gravity of the new search region iteratively to acquire centers of gravity of a plurality of search regions; and determining the lane line in accordance with the centers of gravity of the plurality of search regions.