Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm
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, traff...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | fas |
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University of Tehran
2022-03-01
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| Series: | Journal of Information Technology Management |
| Subjects: | |
| Online Access: | https://jitm.ut.ac.ir/article_86665_90f87be9bf0cccd684906295e0b7452e.pdf |
| _version_ | 1811307080543371264 |
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| author | Sandeep Kumar A Shailu Arpit Jain Nageswara Rao Moparthi |
| author_facet | Sandeep Kumar A Shailu Arpit Jain Nageswara Rao Moparthi |
| author_sort | Sandeep Kumar |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T08:57:08Z |
| format | Article |
| id | doaj.art-ea51da052c2149fe8ea00996f05b3878 |
| institution | Directory Open Access Journal |
| issn | 2008-5893 2423-5059 |
| language | fas |
| last_indexed | 2024-04-13T08:57:08Z |
| publishDate | 2022-03-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Information Technology Management |
| spelling | doaj.art-ea51da052c2149fe8ea00996f05b38782022-12-22T02:53:15ZfasUniversity of TehranJournal of Information Technology Management2008-58932423-50592022-03-0114Security and Resource Management challenges for Internet of Things18019910.22059/jitm.2022.8666586665Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search AlgorithmSandeep Kumar0A Shailu1Arpit Jain2Nageswara Rao Moparthi3Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, India.M.Tech. Scholar, Dept of ECE, Sreyas Institute of Engineering and Technology, Hyderabad, In-dia.Associate Professor, Faculty of Engineering & Computing Sciences, Teerthanker Mahaveer Uni-versity, Moradabad, U.P, India.Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, IndiaDay 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.https://jitm.ut.ac.ir/article_86665_90f87be9bf0cccd684906295e0b7452e.pdfbackground subtractionmerge sort algorithmbinary search algorithmextended kalman filterobject detectionobject prediction and correction |
| spellingShingle | Sandeep Kumar A Shailu Arpit Jain Nageswara Rao Moparthi Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm Journal of Information Technology Management background subtraction merge sort algorithm binary search algorithm extended kalman filter object detection object prediction and correction |
| title | Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm |
| title_full | Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm |
| title_fullStr | Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm |
| title_full_unstemmed | Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm |
| title_short | Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm |
| title_sort | enhanced method of object tracing using extended kalman filter via binary search algorithm |
| topic | background subtraction merge sort algorithm binary search algorithm extended kalman filter object detection object prediction and correction |
| url | https://jitm.ut.ac.ir/article_86665_90f87be9bf0cccd684906295e0b7452e.pdf |
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