ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Journal Article
Publisher : Procedia Computer Science.
Source : Procedia Computer Science, Volume 143, p.493 - 501 (2018)
Keywords : Animal intrusion, Gabor filter, Support vector machines, Watershed Algorithm.
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2018
Abstract : Animal intrusion in agricultural fields has been a pestering problem for farmers, especially during monsoon when they try to maximize their yield. This paper puts forth an image processing and machine learning based approach to classify the animal as threat and hence alert the farmer. The image is segmented into parts using Watershed algorithm. The features are extracted from the training set by using 2D Gabor filter bank. Classification is done using Support Vector Machines algorithm. Percentage accuracy for each test image is analyzed. Training set has been increased in a step wise manner in order to find the minimum possible combination of test images and filter bank and hence increase the efficiency of the model compared to the existing models.
Cite this Research Publication : S. Radhakrishnan and Ramanathan, R., “A Support Vector Machine with Gabor Features for Animal Intrusion Detection in Agriculture Fields”, Procedia Computer Science, vol. 143, pp. 493 - 501, 2018.