Deakin University
Browse

File(s) under permanent embargo

An efficient hybrid algorithm for fire flame detection

Version 2 2024-06-04, 02:17
Version 1 2016-03-31, 09:41
conference contribution
posted on 2024-06-04, 02:17 authored by A Khatami, S Mirghasemi, Abbas KhosraviAbbas Khosravi, S Nahavandi
Proposing efficient methods for fire protection is becoming more and more important, because a small flame of fire may cause huge problems in social safety. In this paper, an effective fire flame detection method is investigated. This fire detection method includes four main stages: in the first step, a linear transformation is applied to convert red, green, and blue (RGB) color space through a 3*3 matrix to a new color space. In the next step, fuzzy c-mean clustering method (FCM) is used to distinguish between fire flame and non-fire flame pixels. Particle Swarm Optimization algorithm (PSO) is also utilized in the last step to decrease the error value measured by FCM after conversion. Finally, we apply Otsu threshold method to the new converted images to make a binary picture. Empirical results show the strength, accuracy and fast-response of the proposed algorithm in detecting fire flames in color images.

History

Pagination

1-6

Location

Killarney, Ireland

Start date

2015-07-12

End date

2015-07-17

ISSN

2161-4393

ISBN-13

9781479919604

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

IJCNN 2015: Proceedings of the 2015 International Joint Conference on Neural Networks

Event

International Joint Conference on Neural Networks (2015: Killarney, Ireland)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC