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.
An Early Fire Detection Method Based on Smoke Texture Analysis and Discrimination
2008 Congress on Image and Signal Processing ; 3 ; 95-99
2008-05-01
413717 byte
Conference paper
Electronic Resource
English