Real time traffic classification and volume count using automated image processing
Loading...
Supplementary material
Other Title
Authors
Bahri, Intan
Ibrahim, A.
Sian, T.L.
Keong , K.W.
Kamaruddin, A.
Yahaya, N.
Ismail, A.
Ibrahim, A.
Sian, T.L.
Keong , K.W.
Kamaruddin, A.
Yahaya, N.
Ismail, A.
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2024-07
Supervisors
Type
Conference Contribution - Oral Presentation
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
traffic flows
vehicle detection
traffic management
image processing
image classification
unsupervised image classification
vehicle detection
traffic management
image processing
image classification
unsupervised image classification
ANZSRC Field of Research Code (2020)
Citation
Bahri, I., Ibrahim, A., Sian, T.L., Keong, K.W., Kamaruddin, A., Yahaya, N. & Ismail. A. (2024, July 11-12). Real time traffic classification and volume count using automated image processing [Paper presentation] 13th International Conference on Computer Engineering and Mathematical Sciences 2024 (ICCEMS 2024), Istanbul, Turkiye.
https://hdl.handle.net/10652/6710
Abstract
OBJECTIVE
Implement a system able to detect the movement, classification, and number of vehicles through analysing fixed camera video footage with the help of image processing techniques.
• Classifies vehicles into three categories
• Uses adaptive approach with Python and OpenCV, implementing Gaussian Mixture Model technique
• Validates with real traffic camera footage
Publisher
Permanent link
Link to ePress publication
DOI
Copyright holder
Authors
Copyright notice
All rights reserved