Application of digital image processing technique in the microstructure analysis and the machinability investigation

OBRABOTKAMETALLOV Vol. 23 No. 4 2021 TECHNOLOGY plt.axis(“off”) plt.imshow(segmented_image) img3 = cv2.hconcat([image1,segmented_image]) cv2.imshow(‘K Means Clustering’,img3) cv2.waitKey(0) # waits until a key is pressed cv2.destroyAllWindows() # destroys the window showing image Appendix: 2 Program Figure 4 shows the microstructure input data and corresponding snap of the segregation of the black and white area as output in Python. Fig. 4. Microstructure and segregation by K-means clustering in Python Con fl icts of Interest The authors declare no con fl ict of interest.  2021 The Authors. Published by Novosibirsk State Technical University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ ).