Menu
Publications
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2015-15-3-365-372
APPLICABILITY ANALYSIS OF THE PHASE CORRELATION ALGORITHM FOR STABILIZATION OF VIDEO FRAMES SEQUENCES FOR CAPILLARY BLOOD FLOW
Read the full article
';
Article in Russian
For citation: Karimov K.A., Volkov M.V. Applicability analysis of the phase correlation algorithm for stabilization of video frames sequences for capillary blood flow. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol.15, no. 3, pp. 365–372.
Abstract
For citation: Karimov K.A., Volkov M.V. Applicability analysis of the phase correlation algorithm for stabilization of video frames sequences for capillary blood flow. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol.15, no. 3, pp. 365–372.
Abstract
Videocapillaroscopy is a convenient and non-invasive method of blood flow parameters recovery in the capillaries. Capillaries position can vary at recorded video sequences due to the registration features of capillary blood flow. Stabilization algorithm of video capillary blood flow based on phase correlation is proposed and researched. This algorithm is compared to the known algorithms of video frames stabilization with full-frame superposition and with key points. Programs, based on discussed algorithms, are compared under processing the experimentally recorded video sequences of human capillaries and under processing of computer-simulated sequences of video frames with the specified offset. The full-frame superposition algorithm provides high quality of stabilization; however, the program based on this algorithm requires significant computational resources. Software implementation of the algorithm based on the detection of the key points is characterized by good performance, but provides low quality of stabilization for video sequences capillary blood flow. Algorithm based on phase correlation method provides high quality of stabilization and program realization of this algorithm requires minimal computational resources. It is shown that the phase correlation algorithm is the most useful for stabilization of video sequences for capillaries blood flow. Obtained findings can be used in the software for biomedical diagnostics.
Keywords: videocapillaroscopy, stabilization algorithms, phase correlation, capillary blood flow, key points.
Acknowledgements. The authors are grateful to employees of the laboratory of peripheral blood circulation and tissue metabolism research (14, Sretensky Boulevard, Moscow) and personally to Konstantin V. Sukhov, the laboratory director, PhD for capillaroscopy materials posted for free access (Internet) and used in this work as the initial data. This work was carried out under the government financial support of the leading universities of the Russian Federation, Grant 074-U01.
References
Acknowledgements. The authors are grateful to employees of the laboratory of peripheral blood circulation and tissue metabolism research (14, Sretensky Boulevard, Moscow) and personally to Konstantin V. Sukhov, the laboratory director, PhD for capillaroscopy materials posted for free access (Internet) and used in this work as the initial data. This work was carried out under the government financial support of the leading universities of the Russian Federation, Grant 074-U01.
References
1. Gurfinkel Y.I., Ishunina A.M. Computerized capillaroscopy as a method of Tanakan therapy efficiency assessment
in diabetes patients. Proceedings of SPIE - The International Society for Optical Engineering,
2000, vol. 3923, pp. 18–23.
2. Cutolo M., Grassi W., Cerinic M.M. Raynaud's phenomenon and the role of capillaroscopy. Arthritis and
Rheumatism, 2003, vol. 48, no. 11, pp. 3023–3030. doi: 10.1002/art.11310
3. Sukhov K.V., Baranov V.V. Komp'yuternaya kapillyaroskopiya: vozmozhnosti funktsional'noi diagnostiki
sostoyaniya perifericheskogo krovoobrashcheniya [Computed capillaroscopy: possibilities of functional assessment
of peripheral blood circulation]. Funktsional'naya Diagnostika, 2011, no. 1, pp. 38–39.
4. Kwon O., Shin J., Paik J. Video stabilization using Kalman filter and phase correlation matching. Lecture
Notes in Computer Science, 2005, vol. 3656 LNCS, pp. 141–148.
5. Chang H.-C., Lai S.-H., Lu K.-R. A robust real-time video stabilization algorithm. Journal of Visual Communication
and Image Representation, 2006, vol. 17, no. 3, pp. 659–673. doi: 10.1016/j.jvcir.2005.10.004
6. Zhu J., Guo B. Video stabilization with sub-image phase correlation. Chinese Optics Letters, 2006, vol. 4,
no. 9, pp. 553–555.
7. Kim S.-K., Kang S.-J., Wang T.-S., Ko S.-J. Feature point classification based global motion estimation for
video stabilization. IEEE Transactions on Consumer Electronics, 2013, vol. 59, no. 1, pp. 267–272. doi:
10.1109/TCE.2013.6490269
8. Pinto B., Anurenjan P.R. Video stabilization using speeded up robust features. Proc. Int. Conf. on Communications
and Signal Processing, ICCSP 2011. Kerala, India, 2011, pp. 527–531.
9. Bay H., Tuytelaars T., Van Gool L. SURF: Speeded up robust features. Lecture Notes in Computer Science,
2006, vol. 3951 LNCS, pp. 404–417. doi: 10.1007/11744023_32
10. Hu R., Shi R., Shen I.-F., Chen W. Video stabilization using scale-invariant features. Proc. 11th Int. Conf.
Information Visualization. Zurich, Switzerland, 2007, pp. 871–876. doi: 10.1109/IV.2007.119
11. Qiao G., Zong G., Wang J., Sun M. Automatic toxic granulation detection and grading based on speeded up
robust features. Cytometry Part A, 2011, vol. 79, no. 11, pp. 887–890. doi: 10.1002/cyto.a.21113
12. Zhang N. Computing parallel speeded-up robust features (P-SURF) via POSIX threads. Lecture Notes in
Computer Science, 2009, vol. 5754 LNCS, pp. 287–296.
13. Pratt W.K. Digital Image Processing. NY, Wiley, 1978.
14. Gonzales R.C., Woods R.E. Digital Image Processing. 2nd ed. Upper Saddle River, Prentice Hall, 2002, 793 p.
15. Martinez-de Dios J.R., Ollero A. A real-time image stabilization system based on Fourier-Mellin transform.
Lecture Notes in Computer Science, 2004, vol. 3211, pp. 376–383.
