Texture is an important property of fire smoke, which is a significant signal for early fire detection. This paper describes a method of analyzing the texture of fire smoke combining two innovative texture analysis tools, Wavelet Analysis and Gray Level Cooccurrence Matrices (GLCM). Tree-Structured Wavelet transform is used to represent the textural images and GLCM are used to compute the different scales of the wavelet transform and to extract the features of fire-smoke texture. The smoke texture and the non-smoke texture are classified by neural network classifier. The discrimination performance is related to the quantity of input vectors.


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    Titel :

    An Early Fire Detection Method Based on Smoke Texture Analysis and Discrimination


    Beteiligte:
    Cui, Yu (Autor:in) / Dong, Hua (Autor:in) / Zhou, Enze (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    413717 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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