TY - JOUR ID - 86665 TI - Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm JO - Journal of Information Technology Management JA - JITM LA - en SN - AU - Kumar, Sandeep AU - Shailu, A AU - Jain, Arpit AU - Moparthi, Nageswara Rao AD - Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, India. AD - M.Tech. Scholar, Dept of ECE, Sreyas Institute of Engineering and Technology, Hyderabad, In-dia. AD - Associate Professor, Faculty of Engineering & Computing Sciences, Teerthanker Mahaveer Uni-versity, Moradabad, U.P, India. AD - Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, India Y1 - 2022 PY - 2022 VL - 14 IS - Special Issue: Security and Resource Management challenges for Internet of Things SP - 180 EP - 199 KW - Background subtraction KW - Merge Sort Algorithm KW - Binary Search Algorithm KW - Extended Kalman filter KW - Object Detection KW - Object Prediction and Correction DO - 10.22059/jitm.2022.86665 N2 - Day by day demand for object tracing is increasing because of the huge scope in real-time applications. Object tracing is one of the difficult issues in the computer vision and video processing field. Nowadays, object tracing is a common problem in many applications specifically video footage, traffic management, video indexing, machine learning, artificial intelligence, and many other related fields. In this paper, the Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm is proposed. Initially, the background subtraction method was used for merge sort and binary search algorithm to identify moving objects from the video. Merge sort is to divide the regions and conquer the algorithm that arranges the region in ascending order. After sorting, the binary search algorithm detects the position of noise in sorted frames and then the next step extended the Kalman Filter algorithm used to predict the moving object. The proposed methodology is linear about the valuation of mean and covariance parameters. Finally, the proposed work considered less time as compared to the state of art methods while tacking the moving objects. Its shows less absolute error and less object tracing error while evaluating the proposed work. UR - https://jitm.ut.ac.ir/article_86665.html L1 - https://jitm.ut.ac.ir/article_86665_90f87be9bf0cccd684906295e0b7452e.pdf ER -