Projects:2016s2-246 Feral Cat Detector

Supervisors

Dr. Danny Gibbins & Dr. Said Al-Sarawi

Group member

Bolun Huang & Yan Chen

Introduction

In Australia, significant numbers of native wildlife are killed each year by feral cats and foxes. As part of their control and monitoring, field researchers and park managers are interested in low cost automated sensor systems that could be placed out in the field to detect the presence of feral cats and possibly even trigger control measures. The aim of this project is to examine a range of image and signal processing techniques that could be used to reliably detect the presence of a nearby feral cat or fox and distinguish it from other native animals such as wallabies and wombats. The possible range of sensors that might be used to achieve this include (but is not limited to) infra-red imaging cameras, ultrasonic detectors, and imaging range sensors (akin to say an x-box Kinect). Both the sensors and the processing unit (say a raspberry pi or A20 based mini board) would need to be low cost and potentially sometime in the future be able to operate in the field for days at a time. The two students would be required to develop both the processing techniques and a simple hardware implementation which demonstrates their solution.

Approach

Based on the project of Richard & Yang in the last year, we build a alternative classification system which consist of two parts: feature selection and classification.