This paper is published in Volume-5, Issue-5, 2019
Area
Electrical Computer Engineering
Author
Sneha Pullanoor
Org/Univ
Independent Researcher, India
Keywords
Anti-poaching, Eigenfaces, Fisher faces, Eigenvalues, Machine learning, Thermal Imaging
Citations
IEEE
Sneha Pullanoor. Eliminating poaching by using machine learning algorithms and thermal imaging, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Sneha Pullanoor (2019). Eliminating poaching by using machine learning algorithms and thermal imaging. International Journal of Advance Research, Ideas and Innovations in Technology, 5(5) www.IJARIIT.com.
MLA
Sneha Pullanoor. "Eliminating poaching by using machine learning algorithms and thermal imaging." International Journal of Advance Research, Ideas and Innovations in Technology 5.5 (2019). www.IJARIIT.com.
Sneha Pullanoor. Eliminating poaching by using machine learning algorithms and thermal imaging, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Sneha Pullanoor (2019). Eliminating poaching by using machine learning algorithms and thermal imaging. International Journal of Advance Research, Ideas and Innovations in Technology, 5(5) www.IJARIIT.com.
MLA
Sneha Pullanoor. "Eliminating poaching by using machine learning algorithms and thermal imaging." International Journal of Advance Research, Ideas and Innovations in Technology 5.5 (2019). www.IJARIIT.com.
Abstract
The project intends to propose a low-cost system that can be used to eradicate poachers in large, restricted areas. Poaching is a huge problem and constantly looking for different methods to eradicate it is in fact very necessary to protect the species from being extinct. The project involves creating an electric pillar-like structure that uses thermal imaging and face recognition techniques to help detect humans and faces in restricted areas. Poachers can be detected at night using thermal imaging techniques. Machine learning algorithms such as Eigenfaces, Eigenvalues, and Fisherfaces are extracted using OpenCV which can be used to detect and store the recognized faces.