Automatic image segmentation for material microstructure characterization by optical microscopy

Naim Ramou, Nabil Chetih, Yamina Boutiche, Rabah Abdelkader

Abstract


This work shows the utility to have a microstructure characterization to analysis the properties of materials.  For this, digital image segmentation is used on microscopic images of materials to extract the number of phases and their proportion present in the material to obtain a quantitative description of material properties and to better control product quality. In this way, we present here an automated method for segmenting the phases present in microscopic scanning images of metallographic samples using a multiphase level set with Mumford Shah formulation. Experience shows that the proposed model successfully detects phase regions for a variety of real micrographic images and provides the required accuracy and robustness to the process..


Full Text:

PDF

References


Moghimi, M.K., Mohanna, F., (2019) A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing. SN Appl. Sci. 1, 1242

https://doi.org/10.1007/s42452-019-1255-0

Joshua P. (2013) Mechanical Properties of Materials. Solid Mechanics and Its Aplications.

Lovell M.C., Avery A.J., Vernon M.W. (1976) Physical Properties of Materials.The Modern University Physics Series.

Laszlo S., Totha b., Chengfan G.C. (2014) Ultrafine-grain metals by severe plastic deformation. Microstructure characterization.92,1–14. [4]Sarkhawas G., Arti B. (2015) Particle Analysis Using Improved Adaptive Level Set Method Based Image Segmentation. International Conference on Computing Communication Control and Automation.Pune. India, 747– 751.

https://doi.org/10.1109/iccubea.2015.149

Mohammadi J., Behnamian Y., Mostafaei A.,et al (2015) Friction stir welding joint of dissimilar materials between AZ31B magnesium and 6061 aluminum alloys:Microstructure studies and mechanical characteri- zations. Microstructure characterization.101,189–207.

https://doi.org/10.1016/j.matchar.2015.01.008

Huang W.,Chai L.,Li Z.,Yang X., Guoc N.,Song B (2016) Evolution of microstructure and grain boundary character distribution of a tin bronze annealed at different temperatures’.Microstructure characteriza- tion.114,204–210.

https://doi.org/10.1016/j.matchar.2016.02.022

Chatterjee O.,Das K.,Dutta S.,Datta S.,Saha S.K. (2010) Phase Extraction and Boundary Removal in Dual Phase Steel Micrographs. IEEE India

https://doi.org/10.1109/indcon.2010.5712693

Murase K.,Sugal S. (2013) Segmentation of dual phase steel micrograph: An automated approach. Measurement.46,2435–2440.

Choudhury, A., Pal, S., Naskar, R. and Basumallick, A. (2019), "Computer vision approach for phase identification from steel microstructure", Engineering Computations, Vol. 36 No. 6, pp. 1913-1933. https://doi.org/10.1108/EC-11-2018-0498

https://doi.org/10.1108/ec-11-2018-0498

Halimi, M. & Ramou, N. (2013) Extraction of weld defects dimension from radiographic images using the level set segmentation without re-initializationRuss J Nondestruct Test 49: 424.

https://doi.org/10.1134/s1061830913070036

Vanderschaeve E.,Taillard R., and Foct J. (1994) Etude des phnomnes de prcipitation dans un acieraustnitique 19% de chrome et 19% de manganse, et ˆrs forte teneur en azote. J. Phys IV. Colloque C3, supplment au Journal de Physique III.4.

https://doi.org/10.1051/jp4:1994312

Zucatto I., Moreira M.C., Machado I.F., And Lebrao S.M.G. (2002) Microstructural Caracterization and The Effect of Phase Transformations on Toughness of The UNS S31803 Duplex Stainless steel Aged treated at 850 C.Materials Research.5(3),385-389.

https://doi.org/10.1590/s1516-14392002000300026

Lacombe P.,Baroux B., Beranger G. (1990) Les aciers inoxydables.

Chen T.H., Weng, K.L. And Yang, J.R. (2002) The Effect Of High Temperature Exposure On The Microstructural Stability And Toughness Property In A 2205 Duplex Stainless Steel.Materials Science And Engi- neering,A 338,259 270.

https://doi.org/10.1016/s0921-5093(02)00093-x

D.Mumford and J. Shah. (1989) Optimal approximation by piecewise

smooth functions and associated variational problems. Communications on Pure and Applied Mathematics.XLII, 577–685.

M. Rousson and R. Deriche. (2002) A Variational Framework for Active and Adaptative Segmentation of Vector Valued Images.Technical Report. 4515.Inria.France.

https://doi.org/10.1109/motion.2002.1182214

Chan T.F. and Vese L.A. (2000) Image segmentation using level sets and the piecewise constant Mumford-Shah model.Tech.Rep. UCLA Dept. Math, CAM 00-14.

Vese L.A. and Chan T.F. (2002) A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model.International Journal of Computer Vision. 50(3),271293.




DOI: https://doi.org/10.31449/inf.v44i3.3034

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.