Developing and validating a simulation model for counting and classification of vehicles
An algorithm system approach has been presented for extracting traffic data using video image processing. While an offline program focuses on extracting vehicles, tracking them and provides the vehicle count for a short period of time. It uses background subtraction, shadow removal, and pixel anal...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2016
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| Online Access: | http://journalarticle.ukm.my/10213/1/4.pdf http://journalarticle.ukm.my/10213/ http://www.ukm.my/jkukm/?page_id=2011 |
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| Summary: | An algorithm system approach has been presented for extracting traffic data using video image processing. While an
offline program focuses on extracting vehicles, tracking them and provides the vehicle count for a short period of time. It
uses background subtraction, shadow removal, and pixel analysis for extracting moving objects. The results show that the
algorithm is capable of counting 95% of the vehicles due to some shaking in the video feed. These data have been analyzed
by statistical regression to show the credibility of the results which been approved to be useful according to the value of
R Square and Significance F compared with the value of the observation method. Also, the classification of vehicles was
performed using the improfile command in Matlab-Video Image Processing that computes the intensity values along a
line or a multiline path in an image. The algorithm program was developed to detect vehicles in traffic videos and get the
vehicle count for the small time period as an assistance tool for a researcher who seeks vehicle counting. |
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