Micro-CT image datasets are used. The de-noising filter is used to remove noise from the image as a pre-processing step, then feature extraction is performed, then the back propagation neural network is created, and finally it changes the weight number of the network and save the output. The proposed algorithm is compared with the Thresholding method and Region Growing method. The results demonstrated that the proposed technique outperforms other methods in terms of speed and accuracy