Embedded Video Surveillance Based Moving Object Detection and Tracking
Dhaya Chinnathambi1, Poonkavithai Kalamegam2
1Dhaya Chinnathambi, Professor, Department of Computer Science and Engineering, Adhiparasakthi Engineering College, Melmaruvathur.
2Poonkavithai Kalamegam, Associate Professor, Department of Computer Science and Engineering , Hindustan University of Science and Technology, Chennai.
Manuscript received on 02 August 2019. | Revised Manuscript received on 09 August 2019. | Manuscript published on 30 September 2019. | PP: 5740-5745 | Volume-8 Issue-3 September 2019 | Retrieval Number: B2601078219/2019©BEIESP | DOI: 10.35940/ijrte.B2601.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Background reckoning and the foreground, play prominent roles in the tasks of visual detection and tracking of objects. Moving Object Detection has been widely used in sundry discipline such as intelligent systems, security systems, video monitoring systems, banking places, provisionary systems, and so on. In this paper proposes moving objects detection and tracking method based on Embedded Video Surveillance. The method is based on using lines computed by a gradient-based optical flow and an edge detector gradient-based optical flow and edges are well matched for accurate computation of velocity, not much attention is paid to creating systems for tracking objects using this feature. The proposed method is compared with a recent work, proving its superior performance and when we want to represent high quality videos and images with, lower bit rate, and also suitable for real-world live video applications. This method reduces influences of foreground objects to the background model. The simulation results show that the background image can be obtained precisely and the moving objects recognition is achieved effectively.
Keywords: Object Detection and Tracking, EVS, Edge Localization, Embedded Software.
Scope of the Article: Embedded and Ubiquitous Software Engineering