It has been proposed to utilize the median algorithm for determination of the extrema positions of diffuse light reflectance intensity distribution by a discrete signal of a photodiode linear array. The algorithm formula has been deduced on the base of piecewise-linear interpolation for signal representation by cumulative function. It has been shown that this formula is much simpler for implementation than known centroid algorithm and the noise immune Blais and Rioux detector algorithm. Also, the methodical systematic errors for zero noise as well as the random errors for full common mode additive noises and uncorrelated noises have been estimated and compared for mentioned algorithms. In these terms, the proposed median algorithm is proportionate to Blais and Rioux algorithm and considerably better then centroid algorithm.

1. Verkhovlyuk, A.M.; Bezpalyi, A.A.; Naymenko, M.I.; Starodub, N.P.; Noga, A.P. Surface defects of products from argentum. Ukrainian Chemistry Journal, 2009, 75, 112-115. (in Ukrainian)

2. Ostash, O.P.; Kondyr, A.I.; Vol'demarov, O.V. et al. Structural microdamageability of steels of the steam pipelines of thermal power plants. Mater Sci 2009, 45. https://doi.org/10.1007/s11003-009-9189-0

3. Baltes, H.; Brand, O.; Fedder, G. K.; Hierold, Ch.; Korvink, J.G.; Tabata, O.; Lohe, D.; Hausselt, J. Microengineering of Metals and Ceramics. Part II: Special Replication Techniques, Automation, and Properties, Vol. 4; Wiley, 2005.

4. Jordan, A. Microstructure Characterization and Corrosion Properties of Two Recycled Aluminium Alloys AA5050 and AA6011, Thesis for the degree of Doctor of Philosophy; University of Manchester, 2016

5. Ivasiv, I.B.; Dzhala, R.M. Peaks' Positions Estimation in Diffuse Light Reflection Sensor's Signal for Pitting Corrosion Detection. Measuring and Computing Techniques in Technological Processes: Proceedings of the XVI International. scientific and technical conference (June 10-15, 2016, Odessa). Odessa - Khmelnytsky, KhNU, 2016, P.50

6. Ivasiv, I.B. Estimation of errors in determining corrosion grain sizes by analysis of diffuse light reflection signal. Information Extraction and Process. 2020, 48(124), 25-34. https://doi.org/10.15407/vidbir2020.48.025

7. Ferguson, J.A.; Sawyers, W.G.; Waddell, K.A.; Ferrige, A.G.; Alecio, R.; Ray, S. Improved centroid peak detection and mass accuracy using a novel, fast data reconstruction method. In Proc. of the 50th ASMS Conf. on Mass Spectrometry and Allied Topics; 2002 June 2-6; Orlando, Florida; ASMS, 2002.

8. Arines, J.; Ares, J. Minimum variance centroid thresholding. Optics Letters; 2002, 27(7), 497-499. https://doi.org/10.1364/OL.27.000497

9. Thomas, S. Optimized centroid computing in a Shack-Hartmann sensor. In Proc. SPIE; 2004, 5490, 3, pp 1238-1246. https://doi.org/10.1117/12.550055

10. Lange, E.; Gropl, C.; Reinert, K.; Kohlbacher, O.; Hildebrandt, A. High-Accuracy Peak Picking of Proteomics Data Using Wavelet Techniques. In Proc. Pacific Symp. on Biocomputing; 2006 (January 3-7, 2006, Maui, Hawaii, USA). - 2006. - P. 243-254 https://doi.org/10.1142/9789812701626_0023

11. Naidu, D.K.; Fisher, R.B. A Comparison of Algorithms for Subpixel Peak Detection. Image Technology. In Advances in Image Processing, Multimedia and Machine Vision, Jorge L. C. Sanz, Ed.; Springer: Berlin, Heidelberg, 1996.

12. Blais, F.; Rioux, M. Real-Time Numerical Peak Detector. Signal Processing; 1986, 11,145-155. https://doi.org/10.1016/0165-1684(86)90033-2

13. Nagaraj, K.; Lewis, S.H.; Walden, R.W. et al. A median peak detecting analog signal processor for hard disk drive servo. IEEE J. of Solid-State Circuits; 1995. 30, 461-470. https://doi.org/10.1109/4.375967