10.14489/td.2017.11.pp.004-011

2017, 11 November

DOI: 10.14489/td.2017.11.pp.004-011

Makhov V. E., Potapov A. I., Shaldaev S. E.
INVESTIGATION OF THE BORDER LIMITS BY THE METHOD OF DISTRIBUTION OF CONTRAST WITH USING THE OPTICAL-ELECTRONIC SYSTEM. PART 2
(pp. 4-11)

Abstract. Background. Optoelectronic systems recording the image of a controlled object are widely used in automated control systems for linear dimensions and product shapes in industry. In practice, under production conditions, it is not always possible to provide sufficient conditions for high-precision measurements, which reduces the efficiency of technological processes. The actual task is the development of measuring tools and algorithms that operate in a wide range of conditions change while monitoring industrial products and process equipment. Materials and/or methods. An algorithmic method of imaging contrast curves of its borders is previously used for measurement information form of products fragments. The method of scanning the profile line in the images of the contrast curves was used to measure the surface shape of product. The method for analyzing the curves of the coefficients of continuous wavelet transform (CWT) is used in the calculation of the image functions boundaries. Mathematical models of the shadow image of controlled of products and virtual instrument (VI) based on the computer technology company National Instruments (NI) is used to research the accuracy of measurements. Results. The method of analysis curve luminance distribution CWT coefficients vertically scanned lines the profile curves image borders contrast allows for more than twice to increase the accuracy of determining the geometric shapes sizes of products in the shadow image. At oblique scanning line profile, including perpendicular to the tangent to the surface of the measurement accuracy increases by 5 times. The horizontal scan line profile allows to determine the coordinate of the jump or fracture shape of the surface to an accuracy of 0.1 pixel. Additional scanning angle of the profile line at each point of measurement eliminates the effect of pixilation and local image defects. Conclusion. Model experiments have shown that the use of CWT algorithms in sections contrast curves can achieve the accuracy of measuring the profile of controlled goods 0.1 pixels. At the same time proved the possibility of determining the coordinates of the jump and fracture the boundaries of the image with an accuracy of 0.1 pixels. The main areas of application of high-precision measurements of geometric forms a shadow image with unilateral or partial access to the measured object.

Keywords: video monitoring system, optoelectronic system, the boundary of the shadow image, continuous wavelet transform (CWT), curves CWT coefficients.

+ - About the Authors Click to collapse

V. E. Makhov (Saint-Petersburg Mining University, Mozhaisky Military Space Academy, St. Petersburg, Russia)
A. I. Potapov (Saint-Petersburg Mining University, St. Petersburg, Russia)
S. E. Shaldaev (Mozhaisky Military Space Academy, St. Petersburg, Russia)

+ - References Click to collapse

1. Prett U. (1982). Digital image processing. Book 1. Moscow: Mir. [in Russian language]
2. Makhov V. E., Potapov A. I. (1989). Heterodyneraster method of quality inspection of products. Defektoskopiia, (10), pp. 68-84. [in Russian language]
3. Safiullin N. T., Porshnev S. V. (2011). Comparative analysis of the instantaneous frequency calculation through the Hilbert transform and direct quadrature. Nauchno-tekhnicheskie vedomosti SPbGPU. Informatika. Telekommunikatsii. Upravlenie, (5), pp. 18-24. [in Russian language]
4. Makhov V. E., Orlov D. V. (2015). Computer technologies of the National Instruments company for vibroacoustic diagnostics of mechanical systems. Komponenty i tekhnologii, (5), pp. 145-149. [in Russian language]
5. Dobeshi I. (2001). Ten lectures on wavelets. Izhevsk: NITs Reguliarnaia i khaoticheskaia dinamika. [in Russian language]
6. Makhov V. E., Potapov A. I. (2013). The measuring optical system in a mechanical instability of the control object. Kontrol'. Diagnostika, (1), pp. 12-21. [in Russian language]
7. Makhov V. E., Potapov A. I. (2011). Use the wavelet analysis for diagnostics of technical sight system. Kontrol'. Diagnostika, (9), pp. 11-18. [in Russian language]
8. Makhov V. E., Potapov A. I. (2013). Research measuring the optical system in a non-mechanical stability of the control object. Kontrol'. Diagnostika, (2), pp. 12-23. [in Russian language]
9. Makhov V. E., Repin O. S., Potapov A. I. (2014). Measurement of linear dimensions of machine vision systems in coherent light. Kontrol'. Diagnostika, (4), pp. 12-19. [in Russian language]
10. Bezuglov D. A., Tsugurian N. O. (2006). Differentiation of measurement results using the mathematical apparatus of wavelet filtration. Izmeritel'naia tekhnika, (4), pp. 12-16. [in Russian language]
11. Makhov V. E. (2010). Using of wavelet analysis algorithms in the study of the kinetics of formation of powder-calcined coatings. Konstruktsii iz kompozitsionnykh materialov, (3), pp. 28-36. [in Russian language]
12. Makhov V. E. (2012). Study of algorithms of wavelet-transform to determine the coordinates of light barriers. Voprosy radioelektroniki. Seriia Tekhnika televideniia, (2), pp. 78-89. [in Russian language]
13. Makhov V. E., Potapov A. I. (2013). Analysis of the efficiency of the optical method of control capillaries. theoretical basis of the optical control of capillaries. Spravochnik. Inzhenernyi zhurnal, (7), pp. 48-56. [in Russian language]
14. Makhov V. E., Potapov A. I., Shaldaev S. E. (2017). Investigation of the border limits by the method of distribution of contrast with using the opticalelectronic system. Part 1. Scientific and methodological principles controlling the image boudaries by contrast allocating. Kontrol'. Diagnostika, (10), pp. 44-51. doi: 10.14489/td.2017.10. pp. 044-051 [in Russian language]
15. Gonsales R., Vuds R. (2005). Digital image processing. Moscow: Tekhnosfera. [in Russian language]
16. Makhov E. M., Potapov A. I., Makhov V. E. (2004). Applied optics: textbook. St. Petersburg: SZTU. [in Russian language]
17. Trevis Dzh., Kring Dzh. (2011). LabVIEW for everyone. 4th Ed. (revised and complemented). Moscow: DMK Press.
18. Klinger T. (2003). Image processing with LabVIEW and IMAQ vision. (National Instruments virtual instrumentation series). Upper Saddle River: Prentice Hall.
19. Liferenko V. D., Zakutaev A., Makhov V. E. (2015). Computer implementation of wavelet analysis methods in the NI LabVIEW development environment. Komponenty i tekhnologii, 170(9), pp. 132-139. [in Russian language]
20. Makhov V. E., Potapov A. I. (2011). Using the algorithm of continuous wavelet transform in vision systems. Izvestiia vuzov. Priborostroenie, 54(9), pp. 10-15. [in Russian language].

+ - Purchase digital version of a single article Click to collapse

This article is available in electronic format (PDF).

The cost of a single article is 350 rubles. (including VAT 18%). After you place an order within a few days, you will receive following documents to your specified e-mail: account on payment and receipt to pay in the bank.

After depositing your payment on our bank account we send you file of the article by e-mail.

To order articles please fill out the form below: