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Traffic Density Analysis based on Image Segmentation with Adaptive Threshold

Luong Anh Tuan Nguyen, Thi-Ngoc-Thanh Nguyen. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Luong Anh Tuan Nguyen, Thi-Ngoc-Thanh Nguyen
10.5120/cae2018652780

Luong Anh Tuan Nguyen and Thi-Ngoc-Thanh Nguyen. Traffic Density Analysis based on Image Segmentation with Adaptive Threshold. Communications on Applied Electronics 7(19):1-7, August 2018. BibTeX

@article{10.5120/cae2018652780,
	author = {Luong Anh Tuan Nguyen and Thi-Ngoc-Thanh Nguyen},
	title = {Traffic Density Analysis based on Image Segmentation with Adaptive Threshold},
	journal = {Communications on Applied Electronics},
	issue_date = {August 2018},
	volume = {7},
	number = {19},
	month = {Aug},
	year = {2018},
	issn = {2394-4714},
	pages = {1-7},
	numpages = {7},
	url = {http://www.caeaccess.org/archives/volume7/number19/822-2018652780},
	doi = {10.5120/cae2018652780},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Traffic congestion has become an important problem in recent years. The main reason is the increase in the population in big cities and respective increase in number of vehicles. Traffic jams not only affect the human routine lives but also lead to a rise in the cost of transportation. So, an automatic traffic control system is required to manage the traffic congestion problem. The traffic density analysis will support the traffic management problems such as intelligent traffic signal control, traffic planning, etc. This paper has proposed a traffic density analysis method based on image segmentation with adaptive threshold. The system was designed and evaluated with the traffic images taken in Ho Chi Minh City, Viet Nam. The proposed method provides a accuracy analysis rate higher than 97% and a verification error lower than 3%.

References

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Keywords

Traffic Density, Otsu threshold, Image Segmentation, Histogram