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Paper Title
Intelligent Farm Surveillance System for Animal Detection in Image Processing using combined GMM and Optical Flow method
Authors
  Akash K. Mehta,  Shital Solanki

Abstract
Intelligent farm surveillance system takes us to video level processing techniques to identify the objects from farms video. Many developed countries as well as developing countries are using intelligent farm surveillance system so that they can view the farm remotely from anywhere. In this thesis we are taking some of the videos from farm surveillance system and from that we detect animals and as the camera detects animal, alarm will ring. This can be useful to protect the farm from crop hazard by animals. In this thesis there is a brief survey of different object detection techniques as well as many background subtraction techniques like frame differencing, Kalman filter, single and mixture of Gaussian model, Optical Flow method and Combination of Gaussian mixture and Optical flow methods. Further for identifying object as animal there are different techniques like template matching, contour based technique, skeleton extraction, edge based technique, etc. But after survey of different methods and combining best feature of them, the system is proposed for animal detection. We use normalized cross correlation method for template matching to identify an object as animal. Proposed system uses the combination of Gaussian mixture model and Optical flow method for background subtraction.

Keywords- Surveillance, GMM, Optical Flow, Image Processing
Publication Details
Unique Identification Number - IJEDR1402198
Page Number(s) - 2538-2543
Pubished in - Volume 2 | Issue 2 | June 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Akash K. Mehta,  Shital Solanki,   "Intelligent Farm Surveillance System for Animal Detection in Image Processing using combined GMM and Optical Flow method", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 2, pp.2538-2543, June 2014, Available at :http://www.ijedr.org/papers/IJEDR1402198.pdf
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