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

Lane line automatic detection method based on AI technology in traffic law enforcement image

An automatic detection and lane line technology, applied in the field of deep learning target detection, can solve problems such as difficulty in lane line labeling, and achieve the effect of fast prediction speed, low requirements, and fast detection speed

Pending Publication Date: 2020-12-08
HANGZHOU DIANZI UNIV
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the difficult problem of labeling lane lines in the prior art, and provide a method for automatic detection of lane lines based on AI technology in traffic law enforcement images

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 line automatic detection method based on AI technology in traffic law enforcement image
  • Lane line automatic detection method based on AI technology in traffic law enforcement image
  • Lane line automatic detection method based on AI technology in traffic law enforcement image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0082] In the embodiment, the data used is the illegal image data in the actual traffic scene, which comes from the influence of the illegal intersection at the intersection captured by the camera above the intersection. The specific steps of the lane marking automatic detection method are as follows:

[0083] Step 1. Production of dataset

[0084] 1. Use the Labelme labeling tool to label the illegal images in the data set. Different from target detection and semantic segmentation, this method only labels the lane line (labeled in the form of a line segment, and only records the two endpoints of the line segment, which are the upper endpoints respectively. and the lower endpoint, which are represented by top and bottom respectively below).

[0085] One of the raw data in this embodiment is as figure 2 As shown, its label data is as follows image 3 shown. The final annotation file information generated mainly includes the picture name, the total number of objects, and th...

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 discloses a lane line automatic detection method based on AI technology in a traffic law enforcement image, and belongs to the field of image identification. Therefore, the method only predicts the two endpoints of the lane line, the endpoint feature point pairs are combined and analyzed according to the specificity of the lane line, and finally the beneficial effects of being smallin labeling workload, low in requirement, high in prediction speed and accurate in prediction are achieved. The method is high in detection speed and high in accuracy. The detection result can be applied to vehicle illegal lane change detection (compacted line detection), and can also be applied to actual scene applications needing to use image data to detect lane line positions, such as lane number judgment and the like.

Description

technical field [0001] The invention belongs to the field of target detection of deep learning, and in particular relates to an automatic detection method of lane lines based on AI technology in traffic law enforcement images. Background technique [0002] Lane line recognition technology has been studied for a long time. He / Rong et al. used Canny operator for edge detection and Hough transform method for lane line detection. The time complexity is high, and the scope of application of the lane line detection is small. It is lane line detection for unmanned driving data, and it only focuses on the left and right lanes. The scenarios targeted by the above recognition methods are lane line detection in automatic driving. In recent years, with the improvement of traffic facilities and illegal capture systems, the occurrence of traffic accidents has been reduced to a certain extent. However, its illegal data is manually screened to classify illegal and non-illegal data. The a...

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): G06T7/90G06T3/40G06N3/04G06K9/62G06K9/46
CPCG06T7/90G06T3/4084G06T2207/30256G06T2207/30204G06V10/44G06N3/045G06F18/214
Inventor 李万清刘俊林永杰袁友伟
Owner HANGZHOU DIANZI UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com