Modified block-matching algorithm for moving object tracking in video surveillance

Author:

Vasekar Shridevi Sukhadeo1ORCID,Shah Sanjeevani K.2

Affiliation:

1. Department of Electronics & Telecommunication Engineering, Pune Institute of Computer Technology, Pune, India

2. Department of Electronics and Telecommunication Engineering, Smt. Kashibai Navale College of Engineering, Pune, India

Abstract

Video surveillance has risen as one of the most promising methods for people who live alone in their dwellings. Few video surveillance innovations have recently been introduced. However, due to various changes in illumination, abrupt shifts in target appearance, identical non-target artifacts in the background, and occlusions, developing a reliable video surveillance algorithm remains a difficult challenge. This work attempts to introduce a new framework for moving object detection and tracking by following four major phases: “Video-to-Frame Conversion, Pre-Processing, Background Subtraction, Feature-Based Multi-object Detection, Multi-object Tracking by Filtering”. Initially, in the Video-to-Frame Conversion process, the recorded input video clips are transformed into distinct frames. During pre-processing, the noise is removed from the video frame using a filtering approach, and thereby the nature of the images will be enhanced. In the proposed work, a Weiner filter is used to remove noise and other undesirable features during the pre-processing. Then, to distinguish the frontal areas of objects, background subtraction is performed using the neutrosophic set in noiseless video frames (pre-processed frames). The objects in the background-subtracted frames are separated using Improved Region Growing (IRG) segmentation model in the Feature-Based Multi-object Detection phase. The objects in the frames are determined from this segmented image. The Modified Full Search Algorithm is being used to track the object (motion estimation) on the video frame after it has been identified in the segmented phase. The Modified full search block matching algorithm (MFSA) is introduced in this research work to find the appropriate mobility. Promising results have been obtained by the proposed work, and also the mathematical excellence of the new method is also proven over other state-of-the-art models.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Computer Science Applications,Modeling and Simulation,General Engineering,General Mathematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3