Key Technologies for Industrial Furnace Temperature Detection Considering Wavelet Texture Features of Image Color
The temperature detection of industrial furnaces is of great significance for the analysis of their operating status.Therefore,a tem-perature detection method for industrial furnaces is proposed that considers the wavelet texture features of image color.Firstly,combining Ret-inex algorithm and TopHat transform to enhance the industrial furnace image and improve the accuracy of feature extraction;Secondly,based on the color space transformation of the image,the color features of the industrial furnace image are obtained,and the color wavelet texture features of the industrial furnace image are obtained on the basis of wavelet transform;Finally,input color wavelet texture features into the least squares support vector machine to achieve temperature detection of industrial furnaces.The experimental results show that the proposed method has significant image enhancement effect,high temperature detection accuracy,and a temperature detection time controlled within 0.3 seconds.Effectively improving the temperature detection effect of industrial furnaces has high practicality.
TopHat transformationRetinex algorithmwavelet transformindustrial furnace temperature detectionleast squares support vector machine