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Estimating the Parameters of Images and Signals by Morphological Analysis

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Measurement Techniques Aims and scope

The basic principle of morphological analysis of images and signals is formulated. The concept of shape, defined as an invariant of signal transformations that model changes in the detection conditions, is basic to the method. Parameters of the signal shape in the form of estimation sets are analyzed.

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References

  1. J. Serra, Image Analysis and Mathematical Morphology, Academic Press, London (1982).

    MATH  Google Scholar 

  2. A. Y. Yakimovskii, “Boundary and object detection in real world images,” J. Assoc. Comp. Mach., No. 23, 599–618 (1976).

  3. N. Ayache, O. Faugeas, and D. Hyper, “A new approach for the recognition and positioning of two-dimensional objects,” IEEE Trans. Pattern Anal. Mach. Intell., No. 8(1), 44–54 (1986).

  4. E. R. Davies, “Locating objects from their point features using an optimized Hough-like accumulation technique,” Patt. Recogn., No. 13(2), 112–121 (1992).

  5. V. A. Vittikh, V. V. Sergeev, and V. A. Soifer, Image Processing in Automatic Scientific Research Systems, Nauka, Moscow (1982).

    Google Scholar 

  6. Yu. Visilter, S. Zheltov, and A. Stepanov, “Object detection and recognition using events-based image analysis,” Proc. SPIE, 2823, 184–195 (1996).

    Article  ADS  Google Scholar 

  7. A. Forsythe and G. Pons, Computer Vision. A Modern Approach [Russian translation], Vil’yams, Moscow (2004).

    Google Scholar 

  8. E. R. Dougherty, “The dual representation of gray-scale morphological,” IEEE Trans. PA MI (1989).

  9. Yu. P. Pyt’ev, “Morphological concepts in image analysis problems,” Dokl. AN SSSR, 224, No. 6, 1283–1286 (1975).

    MathSciNet  MATH  Google Scholar 

  10. Yu. P. Pyt’ev, “Morphological analysis of images,” Dokl. AN SSSR, 269, No. 5, 1061–1064 (1983).

    MathSciNet  MATH  Google Scholar 

  11. Yu. P. Pyt’ev and A. I. Chulichkov, Techniques for Morphological Analysis of Images, FIZMATLIT, Moscow (2010).

    Google Scholar 

  12. S. N. Kulichkov, A. I. Chulichkov, and D. A. Demin, Morphological Analysis of Infrasonic Signals in Acoustics, Izd. Novyi Akropol, Moscow (2010).

    Google Scholar 

  13. Yu. P. Pyt’ev, “Indirect projectors and relative shapes in image morphology,” Zh. Vychisl. Mat. Mat. Fiz., 53, No. 12, 154–176 (2013).

    MathSciNet  Google Scholar 

  14. Yu. V. Vizilter, “Design of morphological operators based on selective morphology,” Proc. SPIE, 4667, 215–226 (2002).

    Article  ADS  Google Scholar 

  15. Yu. V. Vizil’ter and S. Yu. Zheltov, “Comparison and localization of fragments of images using projective morphology,” Vest. Komp. Inf. Tekhnol., No. 2, 14–22 (2008).

  16. Yu. V. Vizil’ter and S. Yu. Zheltov, “Projective morphologies and their applications in structural analysis of digital images,” Izv. RAN TiSU, No. 6, 13–128 (2008).

  17. Yu. V. Vizil’ter and S. Yu. Zheltov, “Use of projective morphologies in detection and identifi cation of objects in images,” Teor. Sist. Upravl., No. 2, 125–138 (2009).

  18. Yu. P. Pyt’ev, Possibility as an Alternative to Probability, FIZMATLIT, Moscow (2016).

    Google Scholar 

  19. Yu. V. Vizil’ter, “Structural filtering of digital images using projective morphologies,” Vest. Komp. Inf. Tekhnol., No. 5, 18–22 (2008).

  20. Yu. V. Vizil’ter, “Generalized projective morphology,” Komp. Optika, 32 (4), 384–386 (2008).

    Google Scholar 

  21. Yu. V. Vizil’ter, S. Yu. Zheltov, A. V. Bondarenko, et al., Image Processing and Analysis in Machine Vision Problems. A Course of Lectures and Practical Exercises, Fizmatkniga, Moscow (2010).

    Google Scholar 

  22. A. I. Chulichkov, “Sets for estimating the shape parameter of a signal,” in: Intellectual Systems and Computer Science: Proc. 9th Int. Conf., Izd. Mekh.-Mat. Fak. MGU, Moscow (2006), Vol. 1, Part 2, pp. 310–313.

  23. Yu. P. Pyt’ev, Mathematical Modelling Methods for Measurement-Computational Systems, FIZMATLIT, Moscow (2012).

    MATH  Google Scholar 

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This work was supported by the Russian Foundation for Basic Research (Project No. 14-07-00409).

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Correspondence to Yu. P. Pyt’ev.

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Translated from Izmeritel’naya Tekhnika, No. 6, pp. 23–26, June, 2016.

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Pyt’ev, Y.P., Chulichkov, A.I. Estimating the Parameters of Images and Signals by Morphological Analysis. Meas Tech 59, 584–588 (2016). https://doi.org/10.1007/s11018-016-1012-3

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  • DOI: https://doi.org/10.1007/s11018-016-1012-3

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