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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    Title :

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


    Contributors:
    Cui, Yu (author) / Dong, Hua (author) / Zhou, Enze (author)


    Publication date :

    2008-05-01


    Size :

    413717 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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