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

Smoky vehicle detection method based on multi-scale block LBP and hidden Markov model

A detection method and multi-scale technology, applied in the field of image processing and fireworks detection, to achieve the effect of improving detection efficiency, improving accuracy and reducing false alarm rate

Active Publication Date: 2021-11-19
SOUTHEAST UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a smoky car detection method based on multi-scale block LBP and hidden Markov model, which can make up for the low efficiency of traditional manual monitoring of smoky cars and fully describe the key areas Dynamic features to reduce false positive rate

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
  • Smoky vehicle detection method based on multi-scale block LBP and hidden Markov model
  • Smoky vehicle detection method based on multi-scale block LBP and hidden Markov model
  • Smoky vehicle detection method based on multi-scale block LBP and hidden Markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The detailed process of the inventive method will be clearly and completely described below with reference to the accompanying drawings and embodiments of the description.

[0049] The present invention provides a black smoke vehicle detection method based on multi-scale block LBP and hidden Markov model, and its flow chart is as follows: figure 1 shown, follow the steps below:

[0050] Step 1: Detect moving objects and determine key areas from surveillance video;

[0051] Step 2: Extract multi-scale block LBP features to increase scale and location information;

[0052] Step 3: Use the Hidden Markov Model to describe the dynamic features of the key area, and divide the current frame into a black smoke frame and a non-smoky frame;

[0053] Step 4: Through the analysis of the video sequence, combined with the distribution characteristics of the black smoke frame, further identify the black smoke vehicle.

[0054] The method for detecting the moving target in the step ...

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 black-smoky vehicle detection method based on multi-scale block LBP and hidden Markov model. The method includes: (1) detecting moving objects and determining key areas from surveillance video; (2) extracting multi-scale block LBP features, adding scale and position information; (3) using hidden Markov model to describe the dynamics of key areas feature, divide the current frame into smoky frames and non-smoky frames; (4) further identify smoky cars by analyzing the video sequence and combining the distribution characteristics of smoky frames. Utilizing the technical solution of the present invention, not only can realize the automatic detection of the black smoke vehicle, improve the detection efficiency, but also use the hidden Markov model to describe the dynamic characteristics of the key area, so as to better reduce the false alarm rate.

Description

technical field [0001] The invention belongs to the technical field of image processing and fireworks detection, in particular to a black smoke vehicle detection method based on multi-scale block LBP and hidden Markov model. Background technique [0002] A smoky vehicle is a highly polluting vehicle whose smoky exhaust not only pollutes the air, but also damages human health. [0003] At present, most of the detection of smoky vehicles still relies on manual road inspection, which is time-consuming and labor-intensive, affects traffic, and is inefficient. Another method is the traditional manual video monitoring method. This method is to set up cameras on the road, and then manually play and view each road video. After finding the video of the black smoke vehicle, edit and save the video, and manually Confirm the license plate of the smoky car in the video. According to the survey, cities using this method need to employ a large number of laborers, and each video needs to ...

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 Patents(China)
IPC IPC(8): G06K9/00G06K9/46
CPCG06V20/40G06V20/54G06V10/40G06V10/467G06V2201/08
Inventor 路小波陶焕杰
Owner SOUTHEAST 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