Incident detection algorithm based on radon transform using high-resolution remote sensing imagery

Seyed Mostafa Mousavi Kahaki, Md. Jan Nordin, Amir Hossein Ashtari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

One of the most important methods to solve the traffic congestion is to detect the incident state in a roadway. This paper describes the development of segmentation methods for road traffic monitoring aims at the acquisition and analysis remote sensing imagery of traffic figures, such as presence and number of vehicles, incident detection and automatic driver warning systems. We propose a strategy for road extraction, vehicle detection and incident detection from remote sensing imagery based on radon transform method. Real time extraction and localization of incident in aerial images is an emerging research area that can be applied to vision-based traffic controlling. The intensity imagery is used to extract the incident from satellite images. Techniques based on neural network, radon transform for angle detection and traffic flow measurements are used for road extraction, vehicle detection and incident detection. The results show that the proposed approach has a good detection performance. The maximum angle of vehicles applied for incident detection is 45° and the best performance of the learning system achieved by 87% for detection rate (DR) and a false alarm rate (FAR) under 18% on 45 aerial images of roadways.

Original languageEnglish
Title of host publicationProceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011 - Bandung
Duration: 17 Jul 201119 Jul 2011

Other

Other2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
CityBandung
Period17/7/1119/7/11

Fingerprint

Radon
Remote sensing
Antennas
Traffic congestion
Alarm systems
Flow measurement
Learning systems
Satellites
Neural networks
Monitoring

Keywords

  • Aerial image analysis
  • Incident detection
  • Radon transform
  • Traffic controlling
  • Vehicle detection

ASJC Scopus subject areas

  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Kahaki, S. M. M., Nordin, M. J., & Ashtari, A. H. (2011). Incident detection algorithm based on radon transform using high-resolution remote sensing imagery. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011 [6021622] https://doi.org/10.1109/ICEEI.2011.6021622

Incident detection algorithm based on radon transform using high-resolution remote sensing imagery. / Kahaki, Seyed Mostafa Mousavi; Nordin, Md. Jan; Ashtari, Amir Hossein.

Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011. 6021622.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kahaki, SMM, Nordin, MJ & Ashtari, AH 2011, Incident detection algorithm based on radon transform using high-resolution remote sensing imagery. in Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011., 6021622, 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011, Bandung, 17/7/11. https://doi.org/10.1109/ICEEI.2011.6021622
Kahaki SMM, Nordin MJ, Ashtari AH. Incident detection algorithm based on radon transform using high-resolution remote sensing imagery. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011. 6021622 https://doi.org/10.1109/ICEEI.2011.6021622
Kahaki, Seyed Mostafa Mousavi ; Nordin, Md. Jan ; Ashtari, Amir Hossein. / Incident detection algorithm based on radon transform using high-resolution remote sensing imagery. Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011. 2011.
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