Skip to main content

Use of Automated Image Analysis in the Study of Mechanisms of the Formation of Nitrided Layers

  • Conference paper
Progress in Automation, Robotics and Measuring Techniques

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 352))

  • 1252 Accesses

Abstract

This paper presents a developed model solution designed to identify material properties, and characteristics of the manufacturing processes of surface layers, based on automatic image analysis of material microsections. The characteristics of the mechanisms of formation of nitrided layers, and those occuring during the process phenomena are discussed. The objectives of the use of the methods of digital image processing, and analysis, as well as specific sets of tasks are described. Among presented possibilities of the use of methods of digital image processing, and analysis, the following techniques are discussed: improving the quality of images, segmentation, morphological transformations, and pattern recognition. The presented model includes different stages of the analysis, such as: automatic selection of procedures involving the specified methods of image processing, and analysis, automatic identification of nitriding zones, and their characteristics, automatic identification of technology, and the characteristics of the gas nitriding process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wach, P., Michalski, J., Tacikowski, J., Kowalski, S., Betiuk, M.: Gas nitriding and its variations in industrial applications. Inżynieria Materiałowa 29(6), 808–811 (2008)

    Google Scholar 

  2. Ratajski, J.: Monitoring the growth of the nitrided layer by the magnetic sensor – application examples. Inżynieria Powierzchni 1, 56–64 (2001)

    Google Scholar 

  3. Figiel, W., Kawalec-Latała, E.: Use of image processing and analysis to interpret sections of synthetic acoustic pseudoimpedance. Gospodarka Surowcami Mineralnymi 24(2/3), 371–385 (2008)

    Google Scholar 

  4. Stawowy, M.: Use of image analysis to solve transportation issues. Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk 862, 3–33 (1998)

    Google Scholar 

  5. Jinshan, T., Peli, E., Acton, S.: Image enhancement using a contrast measure in the compressed domain. Signal Processing Letters IEEE 10(10), 289–292 (2003)

    Article  Google Scholar 

  6. Nieniewski, M.: Segmentation of digital images: watershed segmentation method. Akademicka Oficyna Wydawnicza Exit. Warsaw (2005) (in Polish)

    Google Scholar 

  7. Nagabhushana, S.: Computer Vision and Image Processing. New Age International Publishers, Delhi (2005)

    Google Scholar 

  8. Tanniru, P.: Effects of Pre-processing and Postprocessing on the Watershed Transform. San Jose State University (2007)

    Google Scholar 

  9. Bernsen, J.: Dynamic thresholding of gray-level images. In: Proceedings of the Eighth International Conference on Pattern Recognition, pp. 1251–1255. IEEE Computer Society Press, France (1986)

    Google Scholar 

  10. Tadeusiewicz, R., Korohoda, P.: Computer analysis and image processing. Wydawnictwo Fundacji Postępu Telekomunikacji, Cracow (1997) (in Polish)

    Google Scholar 

  11. Vijay, C., Hooker, J.: Optimization methods for logical inference. John Wiley & Sons, Canada (2011)

    Google Scholar 

  12. Padawitz, P.: Computing in Horn clause theories. Springer Publishing Company, USA (2012)

    Google Scholar 

  13. Moussa, H.: Efficient technique to detect the region of interests in mammogram images. Journal of Computer Science 8, 652–662 (2008)

    Google Scholar 

  14. Stoliński, S., Grabowski, S.: Experimental comparison of the median filters to remove impulse noise from color images. Automatyka 9 (2005) (in Polish)

    Google Scholar 

  15. Gotfryd, M.: Gaussian filter - properties, realisability, use. Elektronika: konstrukcje, technologie, zastosowania 51(4), 88–92 (2010)

    Google Scholar 

  16. Derewnicka, D.: Advanced testing method of nitrided layers after heat treatment. Inżynieria Powierzchni 2, 14–18 (2012)

    Google Scholar 

  17. Kosiński, W., Prokopowicz, P.: Algebra of fuzzy numbers - Applied Mathematics. Matematyka dla Społeczeństwa 46(5), 37–63 (2004)

    Google Scholar 

  18. Antonelli, M.: Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework. International Journal of Approximate Reasoning 50(7), 1066–1080 (2009)

    Article  Google Scholar 

  19. Van Broekhoven, E.: Bernard De Baets: Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions. Fuzzy Sets and Systems 157, 904–918 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  20. van der Heude, P.: X-Ray Photoelectron Spectroscopy. Wiley & Sons, Canada (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tomasz Wójcicki .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Wójcicki, T. (2015). Use of Automated Image Analysis in the Study of Mechanisms of the Formation of Nitrided Layers. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Progress in Automation, Robotics and Measuring Techniques. Advances in Intelligent Systems and Computing, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-319-15835-8_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-15835-8_35

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15834-1

  • Online ISBN: 978-3-319-15835-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics