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http://dx.doi.org/10.13067/JKIECS.2012.7.6.1293

Vehicle Tracking using Euclidean Distance  

Kim, Gyu-Yeong (동의대학교 부산IT융합부품연구소)
Kim, Jae-Ho (부산대학교전자공학과)
Park, Jang-Sik (경성대학교 전자공학과)
Kim, Hyun-Tae (동의대학교 부산IT융합부품연구소)
Yu, Yun-Sik (동의대학교 부산IT융합부품연구소)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.7, no.6, 2012 , pp. 1293-1299 More about this Journal
Abstract
In this paper, a real-time vehicle detection and tracking algorithms is proposed. The vehicle detection could be processed using GMM (Gaussian Mixture Model) algorithm and mathematical morphological processing with HD CCTV camera images. The vehicle tracking based on separated vehicle object was performed using Euclidean distance between detected object. In more detail, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the next stage, candidated objects were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations dependent on distance and vehicle type in tunnel. The vehicle tracking performed using Euclidean distance between the objects in the video frames. Through computer simulation using recoded real video signal in tunnel, it is shown that the proposed system works well.
Keywords
Gaussian Mixture Model(GMM); Mathematical Morphology; Euclidean Distance; Vehicle Tracking;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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