Lin Li
Wuhan University of Technology

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Indonesian Journal of Electrical Engineering and Computer Science

Moving Vehicle Recognition and Feature Extraction From Tunnel Monitoring Videos Aiyan Lu; Luo Zhong; Lin Li; Qingbo Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

 In recent decades, many government agencies and famous universities are researching the intelligent traffic video monitoring system. According to the tunnel monitoring video, this paper uses the combination of background subtraction method and three frame differencing method for moving vehicle detection , and designs the geometric parameters and combined parameters for vehicle classification, finally makes up a vehicle classifier, based on these characteristics parameters. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3465 
Traffic Prediction Based on SVM Training Sample Divided by Time Lingli Li; Hongxia Xia; Lin Li; Qingbo Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In recent years, the volume of traffic is rapidly increasing. When vehicles running through the tunnel are more intensive or move slowly, the tunnel environment occurs deteriorated sharply, which affects the normal operation of the vehicle in the tunnel. This paper uses the result of previous mining association rules to select feature items and to establish four training samples divided by time. Then the training samples are utilized to create the SVM classification model. Finally the trained SVM model is used to prediction the tunnel traffic situation. Through traffic situation prediction, effective decisions can be made before traffic jams, and ensure that the tunnel traffic is normal. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3656