Images segmentation by the fuzzy clustering algorithm using texture-fractal features values estimates

V.А. Kuznetsov; А.N. Pototskiy

doi:10.18127/j20700784–201808–03

Images segmentation by the fuzzy clustering algorithm using texture-fractal features values estimates

V.А. Kuznetsov¹, А.N. Pototskiy²

research article UDC 004.931; 004.932 Pages: 27-43 doi.org/10.18127/j20700784–201808–03

¹ Ph.D. (Eng.), Senior Lecturer, MTSC Air Forces «MAA named professor N.E. Zhukovsky and Y.A. Gagarin» (Voronezh)
² Junior Research Scientist, MTSC Air Forces «MAA named professor N.E. Zhukovsky and Y.A. Gagarin» (Voronezh)

Keywords: image texture texture-fractal feature multifractal signature directional multifractal signature FCM-algorithm

Abstract

The paper considers the question of evaluating the informativeness of a new image tex-ture fractal feature – a directed morphological multifractal signature. Experimental studies were carried out to determine the efficiency of synthesized and real images automated segmentation by the fuzzy c-means algorithm using the developed feature. The obtained results testify to a higher accuracy of image segmentation achieved by using a new texture-fractal feature. Conclusions are drawn about the need to optimize the developed algorithm in order to reduce computational costs.

How to cite

Кузнецов В.А., Потоцкий А.Н. Сегментация изображений алгоритмом нечеткой кластеризации с использованием оценок значений текстурно-фрактальных признаков // Успехи современной радиоэлектроники. 2018. № 8. С. 27–43. DOI: https://doi.org/10.18127/j20700784–201808–03

References

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[1] Tishkin R.V. Myagkie vychisleniya v zadachah segmentacii kosmicheskih izobrazhenij // Cifrovaya obrabotka signalov. 2010. № 3. S. 25–29.

[2] Shkol'nyj L.A., Tolstov E.F., Detkov A.N. Radiolokacionnye sistemy vozdushnoj razvedki, deshifrirovanie radiolokacionnyh izobrazhenij / Pod red. L.A. Shkol'nogo. M.: VVIA. 2008.

[3] Bezdek J.C., Ehrlich R., Full W. FCM: Fuzzy C-Means Algorithm // Computers and Geoscience. 1984. V. 10. № 2. P. 191–203.

[4] Shitova O.V., Puhlyak A.N., Drob E.M. Analiz metodov segmentacii teksturnyh oblastej izobrazhenij v sistemah obrabotki izobrazhenij // Nauchnye vedomosti. Ser. «Istoriya. Politologiya. Ekonomika. Informatika». 2014. № 8 (179). V. 30/1. S. 182–188.

[5] Mandel'brot B.B. Fraktal'naya geometriya prirody / Per. A.R. Logunova. Moskva-Izhevsk: Institut komp'yuternyh issledovanij. 2002.

[6] Potapov A.A., Gulyaev Yu.V., Nikitov S.A., Pahomov A.A., German V.A. Novejshie metody obrabotki izobrazhenij / Pod red. A.A. Potapova. M.: FIZMATLIT. 2008.

[7] Ivanov V.K., Paschenko R.E., Stadnik A.M., Yacevich S.E., Kuchuk G.A. Fraktal'nyj analiz izobrazhenij lesnyh massivov // Uspehi sovremennoj radioelektroniki. 2006. № 12. S. 55–61.

[8] Kuznecov V.A., Potockij A.N. Metod izmereniya napravlennoj morfologicheskoj mul'tifraktal'noj signatury tekstury izobrazhenij // Uspehi sovremennoj radioelektroniki. 2017. № 3. S. 39–52.

[9] Russkin A.B. Sravnitel'nyj analiz metodov izmereniya fraktal'noj razmernosti dvumernyh signalov // Informacionno-izmeritel'nye i upravlyayuschie sistemy. 2009. T. 7. № 9. S. 10–19.

[10] Jacquet G., Ohley W., Fortin C. Bone texture characterization by oriented fractal analysis // In Proceedings of the 18th IEEE on Bioengineering. 1988. P. 22–23.

[11] Malinnikov V. A., Uchaev D.V., Uchaev Dm.V. Metodika polucheniya kanonicheskih spektrov pri mul'tifraktal'nom analize cifrovyh izobrazhenij // Obozrenie prikladnoj i promyshlennoj matematiki. 2006. T. 13. № 3. S. 516–517.

[12] Xia Y., Feng D., Zhao R., Zhang Y. Morphology-Based Multifractal Estimation for Texture Segmentation // IEEE transactions on image processing. 2006. V. 15. № 3. P. 614–622.

[13] Peleg S., Naor J., Hartley R. Multiple resolution texture analysis and classification // IEEE Trans. Pattern Anal. Mach. Intell. 1984. V. 6. № 4. P. 518–523.

[14] Lynch J.A., Hawkess D.J., Bukland-Wright J.C. Analysis of texture in macroradio-graphs of osteoarthritic knees, using the fractal signature // Phys. Med. Biol. 1991. V. 36. № 6. P. 709–722.

[15] Xia Y., Feng D., Zhao R., Zhang Y. Multifractal signature estimation for textured image segmentation // Pattern Recognition Letters. 2010. № 31. P. 163–169.

[16] Potapov A.A. Fraktaly v radiofizike i radiolokacii: topologiya vyborki. Izd. 2–e, pererab. i dop. M.: Universitetskaya kniga. 2005.

[17] Yi W.J., Heo M.S., Lee S. Direct measurement of trabecular bone anisotropy using directional fractal dimension and principal axes of inertia // Oral Surg., Oral Medicine, Oral Pathology, Oral Radiology Endodontics. 2007. № 104. P. 110–116.

[18] Feder E. Fraktaly / Per. Yu.A. Danilova, A. Shukurova. M.: Mir. 1991.

[19] Potapov A.A., Gil'mutdinov A.H., Ushakov P.A. Fraktal'nye elementy i radiosistemy: Fizicheskie aspekty. Monografiya / Pod red. A.A. Potapova. M.: Radiotehnika. 2009.

[20] Karimova L.M., Kruglun O.A., Makarenko I.N., Makarenko N.G. Mul'tifraktal'naya segmentaciya dannyh distancionnogo zondirovaniya // Issledovanie zemli iz kosmosa. 2008. № 3. S. 18–26.

[21] Wu J.J. Analyses and simulation of anisotropic fractal surfaces // Chaos, Solitons and Fractals. 2002. № 13. P. 1791–1806.

[22] Brodatz P. Texture: A Photographic album for artists and designers. Dover, New York. 1966. URL: http://sipi.usc.edu/database/database.

[23] Wolski M., Podsiadlo P., Stachowiak G.W. Directional fractal signature analysis of self-structured surface textures // Tribol Lett. 2012. № 47. P. 323–340.

[24] Demidova L.A., Kirakovskij V.V., Pyl'kin A.N. Prinyatie resheniya v usloviyah neopredelennosti. M.: Goryachaya liniya-Telekom. 2012.

[25] Du G., Yeo T.S. A novel multifractal estimation method and its application to remote image segmentation // IEEE Transactions on geoscience and remote sensing. 2002. V. 40. № 4. P. 980–982.

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