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Abstract
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Article Information:
Object Tracking and Detection in Videos using Block Matching with Intuitionistic Fuzzy Logic (BMIFL) Algorithm
R. Revathi and M. Hemalatha
Corresponding Author: M. Hemalatha
Submitted: December 23, 2012
Accepted: January 14, 2013
Published: October 20, 2013 |
Abstract:
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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.
Key words: Detection, Intuitionistic fuzzy logic, segmantation, object tracking, video tracking, , ,
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Cite this Reference:
R. Revathi and M. Hemalatha, . Object Tracking and Detection in Videos using Block Matching with Intuitionistic Fuzzy Logic (BMIFL) Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (19): 3568-3576.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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