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

Night image characteristic extraction method in intelligent vehicle-mounted anti-collision pre-warning system

A technology of image feature extraction and early warning system, applied in image enhancement, image analysis, image data processing and other directions, can solve complex problems, achieve the effect of multi-data volume, avoid interference, and reduce data processing volume

Inactive Publication Date: 2013-04-03
中国航天科工集团第二研究院二〇七所
View PDF0 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The relative complexity of the method

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
  • Night image characteristic extraction method in intelligent vehicle-mounted anti-collision pre-warning system
  • Night image characteristic extraction method in intelligent vehicle-mounted anti-collision pre-warning system
  • Night image characteristic extraction method in intelligent vehicle-mounted anti-collision pre-warning system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0051] The features of the vehicle ahead in this lane include geometric features, brightness features, and color features. The two taillights of the vehicle in front are the most obvious features in the vehicle body at night, so the present invention selects the taillights as the extracted features.

[0052] A nighttime image feature extraction method in an intelligent vehicle collision avoidance warning system, the method comprises the following steps:

[0053] (1) The intelligent vehicle collision avoidance warning system selects the taillights as the features to be extracted from the color, grayscale and shape features of the vehicle

[0054] Because the system collects grayscale images, the color features of the vehicle are not desirable, and can only be selected from grayscale and shape features. At night, commonly used features such as...

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 belongs to the field of a photoelectric technology, and specifically discloses a night image characteristic extraction method in an intelligent vehicle-mounted anti-collision pre-warning system. The night image characteristic extraction method comprises the following steps of: selecting an automobile tail light as characteristics to be extracted, and then canceling noises of images, carrying out image edge clearness, selecting threshold value and carrying out threshold segmentation by using a series of image processing methods; and selecting an interested region AOI (Automated Optical Inspection) when the characteristics of the automobile tail light are extracted and paired, and expressing a target automobile by a rectangular frame and deducing a distance measuring formula through modeling and a series of transformations after extracting and paring the characteristics of the automobile tail light. According to the night image characteristic extraction method, the characteristics of the automobile tail light are highlighted, extracted and paired by a series of image processing methods so as to locate the special location of a front automobile in a lane and provide reliable data for the intelligent vehicle-mounted anti-collision pre-warning system which calculates the distance between the front automobile and the automobile.

Description

technical field [0001] The invention belongs to the field of optoelectronic technology, and in particular relates to a method for extracting nighttime image features in an intelligent vehicle-mounted anti-collision warning system. Background technique [0002] Intelligent Transportation System ITS (Intelligent Transportation System) refers to the use of modern high-tech to make the transportation system intelligent and greatly improve the traffic capacity of the road network under the existing traffic conditions. ITS is currently a research hotspot in the field of global transportation. Experts hope to use intelligent control technology, computer technology and information communication technology to transform the traditional transportation system to improve the safety of the system. Automobile collision avoidance warning system is a part of intelligent transportation system. It detects obstacles such as vehicles around it when the car is moving, and gives an alarm when the...

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): G06T7/00G06T5/00G06K9/46
Inventor 周刊
Owner 中国航天科工集团第二研究院二〇七所
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