Traffic jam detection method based on video processing
A detection method and video processing technology, which is applied in the field of traffic congestion detection based on video analysis technology, can solve problems such as unsatisfactory vehicle tracking effects, and achieve the effect of assisting in judging traffic congestion status, accurate results, and improving accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0039] Example one: figure 1 It is a flowchart of a method for detecting traffic congestion based on video analysis technology implemented in the present invention, and the data file is a video file containing moving vehicles.
[0040] Step 1: Use the multi-frame image averaging method to obtain the background image of the video surveillance area. Since an increase in the average number of frames will improve the effect of noise elimination, the preferred technical solution is to read in in advance 500 consecutive video images for averaging.
[0041] Step 2: Set up a virtual detection line perpendicular to the driving direction of the vehicle at the edge of the surveillance area where the vehicle enters and exits in the video image. When the vehicle in the video passes through the virtual detection line, the image pixel value at the detection line position will change due to the coverage of the vehicle. When the width of the moving object covering the detection line is greater tha...
Embodiment 2
[0073] Embodiment 2: To illustrate the preference of the H, S, and V block parameters of the HSV histogram in Embodiment 1, this example uses the histogram hue H of the HSV color space to be divided into 8 parts, and the saturation S and the brightness V are respectively Divided into 3 parts. Select the video in the first embodiment, and evaluate the traffic jam state according to the same specific implementation steps. The recognition rates are 91.57% in unblocked state, 89.63% in lightly congested state, 87.26% in congested state, and 89.80% in severely congested state. Basically, various congestion states can also be recognized, but the recognition rate of various congestion states is lower than the first embodiment.
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
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