TITLE:
Animal Classification System Based on Image Processing & Support Vector Machine
AUTHORS:
A. W. D. Udaya Shalika, Lasantha Seneviratne
KEYWORDS:
Image Processing, Support Vector Machine (LIBSVM), Machine Learning, Computer Vision, Object Classification
JOURNAL NAME:
Journal of Computer and Communications,
Vol.4 No.1,
January
15,
2016
ABSTRACT: This project is mainly focused to develop
system for animal researchers & wild life photographers to overcome so many
challenges in their day life today. When they engage in such situation, they
need to be patiently waiting for long hours, maybe several days in whatever location
and under severe weather conditions until capturing what they are interested
in. Also there is a big demand for rare wild life photo graphs. The proposed
method makes the task automatically use microcontroller controlled camera,
image processing and machine learning techniques. First with the aid of
microcontroller and four passive IR sensors system will automatically detect
the presence of animal and rotate the camera toward that direction. Then the
motion detection algorithm will get the animal into middle of the frame and
capture by high end auto focus web cam. Then the captured images send to the PC
and are compared with photograph database to check whether the animal is
exactly the same as the photographer choice. If that captured animal is the exactly
one who need to capture then it will automatically capture more. Though there
are several technologies available none of these are capable of recognizing
what it captures. There is no detection of animal presence in different angles.
Most of available equipment uses a set of PIR sensors and whatever it disturbs
the IR field will automatically be captured and stored. Night time images are
black and white and have less details and clarity due to infrared flash
quality. If the infrared flash is designed for best image quality, range will
be sacrificed. The photographer might be interested in a specific animal but
there is no facility to recognize automatically whether captured animal is the
photographer’s choice or not.