The Segmentation of Ferrography Images: A Brief Survey

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This paper provides a general overview on the developments and progress in the segmentation of ferrography images. The problems experienced with applying traditional image processing methods in the segmentation of wear particles, revealed that it is still a big challenge for intelligent ferrography. This has highlighted the need for combining the segmentation and clustering methods for performing ferrography image analysis. In this paper, some of the developments reported in the literature relating to progress made with wear particle image segmentation are reported and examined as a basis for establishing improved methods of ferrography image analysis.

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427-432

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October 2013

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] B. J. Roylance: Tribol. Int. Vol. 38(10) (2005), p.857.

Google Scholar

[2] Z. Peng: Wear Vol. 252 (2002), p.730.

Google Scholar

[3] N. Eliaz and R. M. Latanision: Corros. Rev. Vol. 25(10) (2007), p.107.

Google Scholar

[4] O. Levi and N. Eliaz: Tribol. Lett. Vol. 36 (2009), p.17.

Google Scholar

[5] G. Stachowiak and P. Podsiadlo: Tribol. Int. Vol. 41(1) (2008), p.34.

Google Scholar

[6] M. S. Laghari, Q. A. Memon, G.A. Khuwaja: Int. J. Inf. Technol. Vol. 1 (2004), p.91.

Google Scholar

[7] G.W. Stachowiak, P. Podsiadlo: Tribol. Int. Vol. 39(12) (2006), p.1615.

Google Scholar

[8] R. Surapol: Tribol. Int. Vol. 38(10) ( 2005), p.871.

Google Scholar

[9] P. Podsiadlo, G.W. Stachowiak: Tribol. Int. Vol. 38(10) (2005), p.887.

Google Scholar

[10] G. W. Stachowiak, P. Podsiadlo: Tribol. Int. Vol. 41(1) (2008), pp.34-43.

Google Scholar

[11] B. J. Roylance, I. A. Albidewi and M. S. Laghari: Lubr. Eng. Vol. 50(2) (1994), p.91.

Google Scholar

[12] S. Zhan, S. S. Zhen and X.G. Hu: J. Hefei University of Technology. Vol. 27 (2004), p.44.

Google Scholar

[13] X. Hu et al.: Pattern Recognition and Image Analysis. Vol. 16(4) (2006), p.644.

Google Scholar

[14] X.Q. Gao, H.F. Zuo and G. Chen: Journal of Nanjing University of Aeronautics and Astronautics. Vol. 33 (2001), p.565.

Google Scholar

[15] G. Chen and H. F. Chen: Acta Automatic Sinica. Vol. 29 (2003), p.791.

Google Scholar

[16] G. Chen and H. F. Zuo: Journal of Computer Aided Design and Computer Graphics. Vol. 14 (2002), p.530.

Google Scholar

[17] G. M. Chen et al.: China Mechanical Engineering. Vol. 17 (2006), p.1576.

Google Scholar

[18] S. Q. Yu and X. J. Dai: Tribology. Vol. 27 (2007), p.467.

Google Scholar

[19] G. Chen and H. F. Zuo: Signal Processing. Vol. 17 (2001), p.449.

Google Scholar

[20] G. Chen and H. F. Zuo: Mini-Microsystem. Vol. 23 (2001), p.721.

Google Scholar

[21] J. C. Fan, M. Z. Yang, J. Li: Journal of Wuhan Automotive Polytechnic University. Vol. 19 (1997), p.9.

Google Scholar

[22] L. Jiang et al.: In 1st International Conference on Modelling and Simulation (2008), p.512.

Google Scholar

[23] F. Xin and Y. J. Fan: Lubrication Engineering. Vol. 33 (2008), p.69.

Google Scholar

[24] J. Q. Wang and X. L. Wang: Lubrication Engineering. Vol. 36(5) (2011), p.48.

Google Scholar

[25] J. Q. Wang et al.: Journal of China University of Mining & Technology (2013), in press.

Google Scholar

[26] J. P. Fu, Z. Q. Liao, P. L. Zhang and C. Z. Wang. Comput. Eng. Applic. Vol 18 (2005), p.204.

Google Scholar

[27] F. Li, C. Xu, G. Q. Ren and J. W. Gao: Journal of Nanjing University of Science and Technology. Vol. 29 (2005), p.70.

Google Scholar

[28] X. Hu, P. Huang and S. Zheng: Int. J. Imag. Sys. Tech. Vol. 17 (2007), p.277.

Google Scholar