Integrating Digital Image Processing and Artificial Neural Network for Estimating Porosity from Thin Section

Porosity estimation from thin section image using digital image processing is critical for petrography study since it gives a brief description on the 2D porosity of the sample. The standard routine uses the binarization process that converts the colour (RGB) image into a binary image using pixel value treshold. The idea is that the treshold value must accomodate all the blue regions correlate to pore and turns it into white in the resulting...