An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming
Due to its wide range of applications, the impact of multimedia in the real world has shown stupendous growth. Texts, images, audio, and video are the different forms of multimedia which are utilized by humans in various applications such as education and surveillance applications. A wide range of r...
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doaj-f0bb38ba666c48aa87793a8ff52b43be2021-09-06T19:40:37ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2019-01-0128111310.1515/jisys-2016-0351An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary ProgrammingShanmugapriya Kumaraperumal0Malar RajaMani Suja Mani1Department of Electronics and Communication Engineering, Lord Jeganath College of Engineering and Technology, Kanyakumari, TamilNadu, IndiaDepartment of Electrical & Electronics Engineering, Narayanaguru Siddhartha College of Engineering, Kanyakumari, TamilNadu, IndiaDue to its wide range of applications, the impact of multimedia in the real world has shown stupendous growth. Texts, images, audio, and video are the different forms of multimedia which are utilized by humans in various applications such as education and surveillance applications. A wide range of research has been carried out, and here in this paper, we propose an object racking with the aid of rough set theory in combination with the eminent soft computing technique evolutionary programming. Initially, the input video is segregated into frames, then the frames that belong to particular shots are identified through the shot segmentation process, and after that the object to be tracked is identified manually. Subsequently, the shape and texture feature is extracted, and then the rough set theory is applied. This is done to identify the presence of object in the frames. Consequently, genetic algorithm (GA) is utilized for the object monitoring process to mark the object with variant color. As a result, the selected object is tracked in an effective manner.https://doi.org/10.1515/jisys-2016-0351object trackingvideoshapetextureevolutionary programming (ep)rough set theory |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shanmugapriya Kumaraperumal Malar RajaMani Suja Mani |
spellingShingle |
Shanmugapriya Kumaraperumal Malar RajaMani Suja Mani An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming Journal of Intelligent Systems object tracking video shape texture evolutionary programming (ep) rough set theory |
author_facet |
Shanmugapriya Kumaraperumal Malar RajaMani Suja Mani |
author_sort |
Shanmugapriya Kumaraperumal |
title |
An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming |
title_short |
An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming |
title_full |
An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming |
title_fullStr |
An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming |
title_full_unstemmed |
An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming |
title_sort |
effective technique to track objects with the aid of rough set theory and evolutionary programming |
publisher |
De Gruyter |
series |
Journal of Intelligent Systems |
issn |
0334-1860 2191-026X |
publishDate |
2019-01-01 |
description |
Due to its wide range of applications, the impact of multimedia in the real world has shown stupendous growth. Texts, images, audio, and video are the different forms of multimedia which are utilized by humans in various applications such as education and surveillance applications. A wide range of research has been carried out, and here in this paper, we propose an object racking with the aid of rough set theory in combination with the eminent soft computing technique evolutionary programming. Initially, the input video is segregated into frames, then the frames that belong to particular shots are identified through the shot segmentation process, and after that the object to be tracked is identified manually. Subsequently, the shape and texture feature is extracted, and then the rough set theory is applied. This is done to identify the presence of object in the frames. Consequently, genetic algorithm (GA) is utilized for the object monitoring process to mark the object with variant color. As a result, the selected object is tracked in an effective manner. |
topic |
object tracking video shape texture evolutionary programming (ep) rough set theory |
url |
https://doi.org/10.1515/jisys-2016-0351 |
work_keys_str_mv |
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