Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Lane detection method and system based on connected region extraction and key point fitting

A technology of Unicom area and lane detection, applied in the field of traffic environment perception, can solve the problems of inability to perceive the traffic environment, and achieve the effect of ensuring perception and understanding

Pending Publication Date: 2022-05-31
HEFEI UNIV OF TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a lane detection method and system based on Unicom area extraction and key point fitting, which solves the problem that the existing traffic environment perception technology cannot be efficiently and accurately carried out in real and complex road conditions. The problem of traffic environment perception

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Lane detection method and system based on connected region extraction and key point fitting
  • Lane detection method and system based on connected region extraction and key point fitting
  • Lane detection method and system based on connected region extraction and key point fitting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] First, see Figure 1-2 , the present invention first proposes a lane detection method based on Unicom region extraction and key point fitting, the method includes:

[0058] S1. Based on the pre-collected traffic image, the lane line segmentation model is used to obtain lane line pixels;

[0059] S2. Perform instance segmentation on the lane line pixels based on the depth-first traversal algorithm to obtain candidate pixel points of the lane line;

[0060] S3. Extract key points of the lane line based on the candidate pixel points of the lane line, and fit a lane line based on the key points of the lane line;

[0061] S4. Extract a convex boundary based on the lane line, and obtain a safe driving area of ​​the traffic image based on the convex boundary.

[0062] In this embodiment, based on the lane detection method and system of Unicom area extraction and key point fitting, the collected traffic images are segmented using the lane line segmentation model to obtain lan...

Embodiment 2

[0107] In the second aspect, the present invention also provides a lane detection system based on Unicom region extraction and key point fitting, the system comprising:

[0108] A lane line pixel acquisition module, configured to acquire lane line pixels using a lane line segmentation model based on pre-collected traffic images;

[0109] The instance segmentation module is used to perform instance segmentation on the lane line pixels based on the depth-first traversal algorithm to obtain candidate pixel points of the lane line;

[0110] A lane line fitting module, configured to extract key points of the lane line based on the candidate pixel points of the lane line, and fit a lane line based on the key points of the lane line;

[0111] A safe driving area extraction module, configured to extract a convex boundary based on the lane line, and obtain a safe driving area of ​​the traffic image based on the convex boundary.

[0112] Optionally, the instance segmentation module per...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a lane detection method and system based on connected region extraction and key point fitting, and relates to the technical field of traffic environment perception. The method comprises the following steps: firstly, acquiring lane line pixels by using a lane line segmentation model based on a pre-acquired traffic image; performing instance segmentation on the pixels of the lane line based on a depth-first traversal algorithm to obtain alternative pixel points of the lane line; then, lane line key points are extracted based on the lane line alternative pixel points, and a lane line is fitted based on the lane line key points; and finally, extracting a convex boundary based on the lane line, and obtaining a safe driving area of the traffic image based on the convex boundary. According to the method, the lane line pixels can be accurately segmented from the complex traffic image, efficient and accurate instance segmentation can be performed on the lane line, the unmanned safe driving area is finally extracted, and the problem that traffic environment perception cannot be efficiently and accurately performed in a real and complex road condition environment in the prior art is solved.

Description

technical field [0001] The invention relates to the technical field of traffic environment perception, in particular to a lane detection method and system based on extraction of connected areas and fitting of key points. Background technique [0002] In unmanned driving technology, the visual environment perception of unmanned vehicles is very important for vehicle navigation and positioning, path planning and motion control. The visual environment perception of unmanned vehicles is the most basic content in unmanned driving and assisted driving, and it is also the premise and basis for unmanned vehicles to make decisions. [0003] In the development of visual environment perception for unmanned vehicles, commonly used environmental perception methods include traffic environment perception methods based on traditional image analysis and traffic environment perception methods based on artificial intelligence and deep learning. Most of the traffic environment perception metho...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/58G06V10/46G06V10/26G06V10/764G06V10/774G06V10/82G06T7/187G06T7/13G06T7/64G06T7/194G06T7/136G06K9/62G06N3/04G06N3/08
CPCG06T7/187G06T7/13G06T7/64G06T7/194G06T7/136G06N3/08G06N3/047G06N3/048G06N3/045G06F18/241G06F18/2411G06F18/2415G06F18/214
Inventor 任明仑吴淑慧
Owner HEFEI UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products