Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm

Autor: Sandeep Kumar, A Shailu, Arpit Jain, Nageswara Rao Moparthi
Jazyk: perština
Rok vydání: 2022
Předmět:
Zdroj: Journal of Information Technology Management, Vol 14, Iss Security and Resource Management challenges for Internet of Things, Pp 180-199 (2022)
Druh dokumentu: article
ISSN: 2008-5893
2423-5059
DOI: 10.22059/jitm.2022.86665
Popis: 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.
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