Deakin University
Browse

File(s) under permanent embargo

Automatic detection of lizards

Version 2 2024-06-04, 05:53
Version 1 2017-03-08, 13:53
conference contribution
posted on 2024-06-04, 05:53 authored by YY Nguwi, Abbas KouzaniAbbas Kouzani, JJ Kumar, Don DriscollDon Driscoll
This paper discusses the use of image processing technique to detect lizards in a video stream. We discuss the categorization of form perception, human perception, and animal perception. The sub-categories of them are briefly discussed. We defragmented the video into a total of 3459 images, some are with only background scene, some contains lizard. We discuss how we apply background subtraction to segment out the lizard, followed by experiments comparing thresholding values and methods. We achieve an encouraging average hit rate of 98% and average computation time of 1.066 seconds.

History

Pagination

300-305

Location

Melbourne, Vic.

Start date

2016-11-30

End date

2016-12-03

ISSN

2325-0682

eISSN

2325-0690

ISBN-13

9781509053469

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2016, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICAMechS 2016 : Proceedings of the 2016 International Conference on Advanced Mechatronic Systems

Event

IEEE Systems, Man, and Cybernetics Society. Conference (2016 : Melbourne, Vic.)

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

Piscataway, N.J.

Series

IEEE Systems, Man, and Cybernetics Society Conference