Surveillance System for Animal Detection in Image Processing Using Combined GMM, Template Matching and Optical Flow Method

  Rumel M S Pir

Using Surveillance systems we get video level processing techniques so that we can recognize the items or objects from any video file. So much of the developed countries and also some developing countries are making use of farm surveillance system so that they can analyze the farm from any place of the world. In this topic we are captivating some videos from farm surveillance system and on the basis of that we perceive animals and as the camera identify animal, alarm rings. It can be very useful to protect the farm from crop exposure by animals. In this topic there is a concise examination of diverse object recognition techniques and also many background subtraction techniques like Kalman filter, frame differencing, Optical Flow method , mixture of Gaussian model, and Combination of GMM and Optical flow methods. Further to identify object as animal there are some special techniques like contour based technique, template matching, edge based technique ,skeleton extraction, etc. But after survey of diverse methods and by combining preeminent attribute of them, the system is projected for animal detection. We use normalized cross correlation method for template matching so that we can identify an item or object as animal. Planned organization uses the Combination of all three GMM, Template Matching and Optical flow method for background subtraction.

Keywords- Template Matching, Surveillance, GMM, Optical Flow, Image Processing, Detection

Unique Identification Number - IJEDR1404012
Page Number(s) - 3438-3443
Pubished in - Volume 2 | Issue 4 | Dec 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Rumel M S Pir,   "Surveillance System for Animal Detection in Image Processing Using Combined GMM, Template Matching and Optical Flow Method", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 4, pp.3438-3443, Dec 2014, Available at :http://www.ijedr.org/papers/IJEDR1404012.pdf