DocumentCode :
3659616
Title :
A vision based motion estimation in underwater images
Author :
Pushpendra Kumar;Sanjeev Kumar;R. Balasubramanian
Author_Institution :
Department of Mathematics, IIT Roorkee, 247667, India
fYear :
2015
Firstpage :
1179
Lastpage :
1184
Abstract :
Motion estimation from underwater images is an active research area of the vision system devoted to the applications of robots. In this paper, a vision based system for tracking the motion of moving objects is presented. The aim of this paper is to give an optimal performance against radiometric features such as non-uniform lighting, blurring and noise. The moving object detection is performed by means of optical flow. The optical flow is determined by minimizing the variational functional. The proposed variational functional combined the global model of Horn and Schunck (1981) and the classical model of Nagel and Enkelmann(1986) as a new regularization functional. The formulated variational function is based on total variation regularization and L1 norm, which is solved by an efficient numerical scheme. This makes the model more robust and preserves discontinuity. Finally, a number of experimental results on several underwater images verify the validity of the proposed algorithm.
Keywords :
"Optical imaging","Optical sensors","Estimation","Computer vision","Integrated optics","Robustness","Lighting"
Publisher :
ieee
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on
Print_ISBN :
978-1-4799-8790-0
Type :
conf
DOI :
10.1109/ICACCI.2015.7275771
Filename :
7275771
Link To Document :
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