AIRCC's International Journal of Computer Science and Information Technology

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


In this paper, feature tracking based and histogram based traffic congestion detection systems are developed. Developed all system are designed to run as real time application. In this work, ORB (Oriented FAST and Rotated BRIEF) feature extraction method have been used to develop feature tracking based traffic congestion solution. ORB is a rotation invariant, fast and resistant to noise method and contains the power of FAST and BRIEF feature extraction methods. Also, two different approaches, which are standard deviation and weighed average, have been applied to find out the congestion information by using histogram of the image to develop histogram based traffic congestion solution. Both systems have been tested on different weather conditions such as cloudy, sunny and rainy to provide various illumination at both daytime and night. For all developed systems performance results are examined to show the advantages and drawbacks of these systems.

Keywords

Traffic Congestion, Feature Extraction, ORB, Histogram.
User
Notifications
Font Size