Method for identifying traffic signal lamps based on multiple classifiers

A traffic signal light and identification method technology, applied in the field of traffic signal identification, can solve problems such as poor generality and applicability

Inactive Publication Date: 2018-02-16
CHONGQING UNIV OF POSTS & TELECOMM
View PDF7 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, this method is accurate, but not widely applicable.

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
  • Method for identifying traffic signal lamps based on multiple classifiers
  • Method for identifying traffic signal lamps based on multiple classifiers
  • Method for identifying traffic signal lamps based on multiple classifiers

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0046] Such as figure 1 , figure 2 Shown, method of the present invention comprises the steps:

[0047] (1) First, fix the camera position for collecting video, install it in the middle part of the rearview mirror of the smart car, 1-1.5 meters away from the ground, the wide-angle range of the camera is greater than 120 degrees, and the resolution of the image is 640*480. The camera captures images of the road in front of the vehicle at a rate of 30 frames per second,

[0048] (2) Preprocess the collected images, including grayscale, filtering, etc. to remove the interference caused by environmental factors, and at the same time, according to the position of traffic lights, set more than 1 / 2 of the image as the region of interest, which can be Reduce the complexity and time of image processing.

[0049] (3) Extract the color area of ​​...

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 relates to a method for identifying traffic signal lamps based on multiple classifiers, which belongs to the technical field of image processing. First, a region of interest of an imageis positioned. Then, a candidate region is extracted according to the red / green color characteristic of traffic signal lamps, the candidate region of the traffic signal lamps is filtered according tothe morphological features, and the HOG features and color features of the candidate region are extracted in turn. Next, multiple binary classification SVM models are trained by making use of sample pictures of traffic signals to construct multiple classifiers based on SVM. The disadvantages of slow calculation and low identification accuracy for identification of multiple targets based on a single classifier can be overcome.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a traffic signal lamp recognition method based on a multi-classifier. Background technique [0002] With the development of society, economy and technology, there are more and more vehicles on the traffic roads, and the road environment is becoming more and more complex, and the subsequent traffic accidents also occur frequently. In order to reduce the occurrence of such situations, intelligent transportation comes into being In intelligent transportation, intelligent vehicles are a key part of intelligent transportation. The emergence of intelligent vehicles helps drivers drive, reduces the frequency of traffic accidents, and makes it possible for people with red and green color blindness to drive. Therefore, for Traffic light recognition is of great significance [0003] To achieve this goal, we must first prepare to find the location of the traffic lights from the comp...

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): G06K9/00G06K9/46G06K9/62
CPCG06V20/584G06V10/56G06V10/462G06V2201/09G06F18/214G06F18/2411
Inventor 朱浩刘智毅吴吉红秦浩舒德伟
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap