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http://dx.doi.org/10.5370/KIEE.2016.65.3.477

Area Classification, Identification and Tracking for Multiple Moving Objects with the Similar Colors  

Lee, Jung Sik (Dept. of Control and Robotics Engineering, Kunsan National University)
Joo, Yung Hoon (Dept. of Control and Robotics Engineering, Kunsan National University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.65, no.3, 2016 , pp. 477-486 More about this Journal
Abstract
This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.
Keywords
Similar color; Area classification; Region of interest; Multiple moving objects; Gaussian mixture model; Intelligent video surveillance system;
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Times Cited By KSCI : 6  (Citation Analysis)
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