Wild-Animal Recognition in Agriculture Farms Using W-COHOG for Agro-Security

Nagaraju Andavarapu, Valli Kumari Vatsavayi
2017 International Journal of Computational Intelligence Research  
Computer Vision is applied in agriculture field for food grading, disease identification of the plants and agro-farms security. Huge crop damage is caused by the wild animal attacks on the agriculture farms. Here are some traditional techniques followed by the local farmers, but which are not effective. This problem can be solved using computer vision techniques. In this paper, we proposed an algorithm to detect animals in a given image. W-CoHOG is a Histogram oriented gradients based feature
more » ... ctor with better accuracy. It is an extension of Co-occurrence Histograms of Oriented Gradients (CoHOG). In this paper LIBLINEAR classifier is used in order to get better accuracy for high dimensional data. The experiments were conducted on two benchmark datasets called Wild-Anim and CamaraTrap dataset. Experimental results prove that W-CoHOG performs better than existing state of the art methods
doi:10.37622/ijcir/13.9.2017.2247-2257 fatcat:b7d2wyh5gnchfhytnckeqhveiu