(48-2) 06 * << * >> * Russian * English * Content * All Issues
  
Discretization of a mathematical model for image analysis based on the optics of spiral beams
 S.A. Kishkin 1, S.P. Kotova 2
 1 MIREA – Russian Technological University,
     119454, Moskow, Russia, Vernadskogo 78-1;
     2 Samara Branch of the Physical Institute RAS,
  443011, Samara, Russia, Novo-Sadovaya 221
  PDF, 1146 kB
DOI: 10.18287/2412-6179-CO-1365
Pages: 204-209.
Full text of article: Russian language.
 
Abstract:
The article briefly  outlines a mathematical model for recognizing contours of the objects of interest  in a raster image. The process of its discretization is discussed in more  detail as part of the development of numerical methods that allow the proposed  model to be implemented using  modern  computer technology, while achieving real-time performance. Explicit mathematical procedures suitable for  writing application software codes are given, an estimate of computational complexity  is obtained, and the possibility of achieving real-time performance is  confirmed. Results of a numerical experiment on the reconstruction of spiral  light beams are presented.
Keywords:
computer optics, machine  vision, image recognition, spiral light beams.
Citation:
  Kishkin SA, Kotova SP.  Discretization of a mathematical model for image analysis based on the optics  of spiral beams. Computer Optics 2024; 48(2): 204-209. DOI: 10.18287/2412-6179-CO-1365.
References:
  - Gallego G, et al. Event-based vision: A survey.  IEEE Trans Pattern Anal Mach Intell 2022; 44(1): 154-180. DOI:  10.1109/TPAMI.2020.3008413.
 
  - Kong Y, Fu Y. Human action recognition and prediction:  A survey. Int J Comput Vis 2022; 130: 1366-1401. DOI:  10.1007/s11263-022-01594-9.
 
  - Stable  Diffusion Public Release. 2022. Source:  <https://stability.ai/blog/stable-diffusion-public-release>.
   
  - Zhang  D, Tan Z. A review of optical neural networks. Appl Sci 2022; 12: 5338. DOI:  10.3390/app12115338.
   
  - Mohan  R, et al. Neural architecture search for dense prediction tasks in computer  vision. Int J Comput Vis 2023; 131: 1784-1807. DOI: 10.1007/s11263-023-01785-y.
   
  - Viering  T, Loog M. The shape of learning curves: A review. IEEE Trans Pattern Anal Mach  Intell 2023; 45(6): 7799-7819. DOI: 10.1109/TPAMI.2022.3220744.
   
  - Volostnikov  VG, Kishkin SA, Kotova SP. Contour analysis and modern optics of Gaussian  beams. Computer Optics 2014: 38(3): 476-481. DOI: 10.18287/0134-2452-2014-38-3-476-481.
   
  - Volostnikov  VG, Kishkin SA, Kotova SP. Analysis of contour images using optics of spiral  beams. Quantum Electron 2018; 48(3): 268-274. DOI: 10.1070/QEL16553.
   
  - Volyar  AV, Abramochkin EG, Akimova YE, Bretsko MV. Reconstruction of stable states of  spiral vortex beams. Computer Optics 2022; 46(1): 5-15. DOI: 10.18287/2412-  6179-CO-1032.
   
  - Volyar  AV, Akimova YaE. Transformations of structurally stable states of spiral beams  subjected to sector perturbations. Computer Optics 2021; 45(6): 789-799. DOI:  10.18287/2412-6179-CO-1009.
   
  - Volyar  AV, Abramochkin EG, Razueva EV, Akimova YaE, Bretsko MV. Structural stability  of spiral beams and fine structure of an energy flow. Computer Optics 2021;  45(4): 482-489. DOI: 10.18287/2412-6179-CO-885.
   
  - Abramochkin  EG, Volostnikov VG. Modern optics of Gaussian beams [In Russian]. Moscow:  “Fizmatlit” Publisher; 2010. ISBN: 978-5-9221-1216-1. 
 
  - IEEE 754-2019. IEEE Standard for floating-point arithmetic. (Revision of  IEEE 754-2008). DOI: 10.1109/IEEESTD.2019.8766229.
 
  
  © 2009, IPSI RAS
  151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: journal@computeroptics.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20