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– 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. Key Words : Similar color, Area classification, Region of interest, Multiple moving objects, Gaussian mixture model, Intelligent video surveillance system†Corresponding Author : Dept. of Control and Robotics Engineering, Kunsan National University, Korea E-mail : yhjoo@kunsan.ac.kr* Dept. of Control and Robotics Engineering, Kunsan National University, Korea Received : November 27, 2015; Accepted : January 27, 2016

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