Efficiency of HSV over RGB Gaussian Mixture Model for Fire Detection

Pavel Chmelar, Abdsamad Benkrid

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Computer Vision based systems have already been proposed to detect fire automatically. To increase the reliability of such systems, Gaussian Mixture Models of fire need to be developed in order to decide if an object in a scene is a fire or no. The models are trained using color images in RGB color model. We, however, believe HSV model is more suitable to present the statistics of a set of colored images precisely. To vindicate this claim, the paper includes a rigorous comparative evaluation of the two aforementioned color models in a fire detection system to demonstrate the superiority of the HSV color model. It makes hence the recommendation of using the latter model in vision based fire detection systems.
    Original languageEnglish
    Title of host publicationRadioelektronika 2014
    Subtitle of host publicationProceedings of the 24th International Conference
    EditorsOldrich Ondracek, Jozef Pucik, Miroslav Hagara
    PublisherIEEE
    Pages1-4
    Number of pages4
    ISBN (Print)978-1-4799-3715-8, 9781479937134
    DOIs
    Publication statusPublished - Apr 2014
    EventRadioelektronika 2014: 24th International Conference - Bratislava, Slovakia
    Duration: 15 Apr 201416 Apr 2014
    http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=33045

    Conference

    ConferenceRadioelektronika 2014
    CountrySlovakia
    CityBratislava
    Period15/04/1416/04/14
    Internet address

    Keywords

    • fire detection system
    • RGB model
    • HSV model
    • Gaussian mixture model

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