Visualization and Estimation of Temperature from Glowing Hot Object by Artificial Neural Network and Image Analysis Technique

This paper proposes alternative technique to estimate temperature of glowing hot objects with application of artificial neural network (ANN) and image analysis techniques. Regardless of using the cutting edge technology or sophisticated sensor such as 2D thermo-imaging equipment, an approximated thermo-imagery of the glowing hot object can be reconstructed by a well-trained ANN model together with image analysis in RGB color space. By training the model with data along the Blackbody locus from the CIE-1931 chromaticity chart and using three normalized individual monochromatic R, G and B images as inputs, the processed image having correlated color temperature (CCT) is finally obtained. Experimental results show that averaging error of the estimated temperature can be achieved with 10% for the reddish-yellowish hot objects and less than 10% for the bright-yellow one respectively.