(41-4) 19 * << * >> * Russian * English * Content * All Issues

Parallel implementation of the informative areas generation method in the spatial spectrum domain
Kravtsova N.S., Paringer R.A., Kupriyanov A.V.

Samara National Research University, Samara, Russia ,
Image Processing Systems Institute оf RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

 PDF 85 kB

DOI: 10.18287/2412-6179-2017-41-4-585-587


This paper proposes a parallel implementation of the image informative segments extraction method. The images are segmented in the spatial spectrum domain. The median energy in each selected segment is viewed upon as an area. For purposes of time savings, a parallel implementation of the algorithm for calculating the areas is developed. The developed approach to the parallel algorithm implementation is tested on a high performance multicore computing system. The experiments have shown that the parallel implementation of the method allows us to obtain a three-fold speedup, which is a good result.

diagnostic crystallogram, spatial spectrum, discriminant analysis, k-NN classification, parallel implementation.

Kravtsova NS, Paringer RA, Kupriyanov AV.  Parallel implementation of the informative areas generation method in the spatial spectrum domain. Computer Optics 2017; 41(4): 585-587. DOI: 10.18287/2412-6179-2017-41-4-585-587.


  1. Levitan U, Umerova A, Abjalilova D. Main types of structural organization of blood serum in chronic hepatitises and liver cirrhosises according to crystallographic studies. Abstracts of XII International Euroasian Congress of Surgery and Gastroenterology 2011; 140.
  2. Bulkina NV, Brill GE, Podelinskaya VT. Crystallographic picture of gingival fluid in normal and inflammatory periodontal diseases [In Russian]. Stomatologiya 2012; 91(4) 16-19.
  3. Bulkina NV, Brill GE, Postnov DE, Podelinskaya VT, Eremin OV. Comparative characteristics of the crystallographic pictures of oral fluid and the fluid of the gingival sulcus or periodontal pockets in the diagnosis of inflammatory periodontal diseases [In Russian]. Russian Journal of Dentistry 2012; 4: 12-16.
  4. Shirokanev AS, Kirsh DV, Kupriyanov AV. Research of an algorithm for crystal lattice parameter identification based on the gradient steepest descent method. Computer Optics 2017; 41(3): 453-460. DOI: 10.18287/2412-6179-2017-41-3-453-460.
  5. Paringer RA, Kupriyanov AV. The method for effective clustering the dendrite crystallogram images. Electronic on-site Proceedings of 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding «OGRW 2014» 2014.
  6. Paringer RA, Kupriyanov AV. Research methods for classification of the crystallogramms images. Proceedings of the 12th international conference «PRIP'2014» 2014; 1: 231-234.
  7. Kravtsova N, Paringer R, Kupriyanov A. Development of methods for crystallogramms images classification based on technique of detection informative areas in the spectral space. CEUR Workshop Proceedings 2016; 1638: 357-363. DOI: 10.18287/1613-0073-2016-1638-357-363.
  8. Gaidel AV, Krasheninnikov VR. Feature selection for diagnozing the osteoporosis by femoral neck X-ray images. Computer Optics 2016; 40(6): 939-946. DOI: 10.18287/2412-6179-2016-40-6-939-946.
  9. Fukunaga K. Introduction to statistical pattern recognition. 2nd ed. San Diego: Academic Press; 1990. ISBN: 978-0-12-269851-7.
  10. Ilyasova NYu, Kupriyanov AV, Paringer RA. Formation features for improving the quality of medical diagnosis based on the discriminant analysis methods. Computer Optics 2014; 38(4): 851-855.
  11. Ilyasova NYu. The discriminative analysis application to refine the diagnostic features of blood vessels images. Optical Memory & Neural Networks 2015; 24(4): 309-313. DOI: 10.3103/S1060992X15040037.
  12. Biryukova E, Paringer R, Kupriyanov A. Development of the effective set of features construction technology for texture image classes discrimination. CEUR Workshop Proceedings 2016; 1638: 263-269. DOI: 10.18287/1613-0073-2016-1638-263-269.

© 2009, IPSI RAS
Institution of Russian Academy of Sciences, Image Processing Systems Institute of RAS, Russia, 443001, Samara, Molodogvardeyskaya Street 151; E-mail: journal@computeroptics.ru; Phones: +7 (846) 332-56-22, Fax: +7 (846) 332-56-20