Research Article | OPEN ACCESS
Object Tracking and Detection in Videos using Block Matching with Intuitionistic Fuzzy Logic (BMIFL) Algorithm
1R. Revathi and 2M. Hemalatha
1Research Scholar, Karpagam Univeristy, Coimbatore
2Department of Computer Science, Karpagam University, Coimbatore
Research Journal of Applied Sciences, Engineering and Technology 2013 19:3568-3576
Received: December 23, 2012 | Accepted: January 14, 2013 | Published: October 20, 2013
Abstract
In this study, an innovative attempt has been made using Attanassov’s Intuitionistic fuzzy set theory for tracking moving objects in video. The main focus of this proposed work is taking an account for handling uncertainty in assignment of membership degree known as hesitation degree using Intuitionistic fuzzy. Many algorithms have been developed to reduce the computational complexity of motion vector estimation. Block matching algorithm for motion estimation is accepted in all the video coding standards proposed till date. In Block Matching Algorithm Full Search Algorithm produces the best result for motion vector estimation. But Full Search algorithm is a time consuming and computationally expensive process. The Challenge is to reduce the computational complexity of Full Search algorithm without losing too much quality at the output. In this study we propose to implement Intuitionistic logic based block Matching Algorithm to overcome the computational complexity. This algorithm performs better than fuzzy logic based Three Step Search algorithm.
Keywords:
Detection, Intuitionistic fuzzy logic, segmantation, object tracking, video tracking,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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