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Ellipse Detection on Embryo Imaging Using Random Sample Consensus (Ransac) Method Based on Arc Segment

Open Access
|Sep 2016

References

  1. M. Meseguer, J. Herrero, A. Tejera, K. M. Hilligse, N. B. Ramsing, and J. Remoh, “The use of morphokinetics as a predictor of embryo implantation,” Human Reproduction, vol. 26, no. 10, pp. 2658–2671,2011.
  2. I. Habibie, A. Bowolaksono, R. Rahmatullah, M. Kurniawan, M. Tawakal, I. Satwika, P. Mursanto, W. Jatmiko, A. Nurhadiyatna, B. Wiweko, and A. Wibowo, “Automatic detection of embryo using particle swarm optimization based hough transform,” in Micro-NanoMechatronics and Human Science (MHS), 2013 International Symposium on, Nov 2013, pp. 1–6.10.1109/MHS.2013.6710446
  3. M. El-Shenawy, “Automatic detection and identification of cells in digital images of day 2 ivf embryos,” Ph.D. dissertation, University of Salford, 2013. [Online]. Available: http://usir.salford.ac.uk/28425/
  4. M. Cicconet, K. Gunsalus, D. Geiger, and M. Werman, “Ellipses from triangles,” in Image Processing (ICIP), 2014 IEEE International Conference on, Oct 2014, pp. 3626–3630.10.1109/ICIP.2014.7025736
  5. C. Wong, S. Lin, T. Ren, and N. Kwok, “A survey on ellipse detection methods,” in Industrial Electronics (ISIE), 2012 IEEE International Symposium on, May 2012, pp. 1105–1110.10.1109/ISIE.2012.6237243
  6. A. Fitzgibbon, M. Pilu, and R. B. Fisher, “Direct least square fitting of ellipses,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 5, pp. 476–480, May 1999.10.1109/34.765658
  7. K. Kanatani and P. Rangarajan, “Hyper least squares fitting of circles and ellipses,” Computational Statistics and Data Analysis, vol. 55, no. 6, pp. 2197 – 2208, 2011.
  8. W. Lu and J. Tan, “Detection of incomplete ellipse in images with strong noise by iterative randomized hough transform (irht),” Pattern Recognition, vol. 41, no. 4, pp. 1268 – 1279, 2008.
  9. H. Cheng, Y. Guo, and Y. Zhang, “A novel hough transform based on eliminating particle swarm optimization and its applications,” Pattern Recognition, vol. 42, no. 9, pp. 1959 – 1969, 2009.
  10. C. Akinlar and C. Topal, “Edcircles: A real-time circle detector with a false detection control,” Pattern Recognition, vol. 46, no. 3, pp. 725 – 740, 2013.10.1016/j.patcog.2012.09.020
  11. C. Fatichah, D. Purwitasari, V. Hariadi, and F. Effendy, “Overlapping white blood cell segmentation and counting on microscopic blood cell images,” International Journal on Smart Sensing and Intelligent Systems, vol. 7, no. 3, pp. 1271–1286, 2014.
  12. Aprinaldi, I. Habibie, R. Rahmatullah, A. Kurniawan, A. Bowolaksono, W. Jatmiko, and B. Wi-weko, “Arcpso: Ellipse detection method using particle swarm optimization and arc combination,” in Advanced Computer Science and Information Systems (ICACSIS), 2014 International Conference on, Oct 2014, pp. 408–413.10.1109/ICACSIS.2014.7065877
  13. A. R. Syulistyo, H. A. Wisesa, Aprinaldi, A. Bowolaksono, B. Wiweko, and W. Jatmiko, “Ellipse detection on embryo image using modification of arc particle swarm optimization (arcpso) based arc segment,” in 2015 International Symposium on Micro-NanoMechatronics and Human Science (MHS),Nov 2015, pp. 1–6.10.1109/MHS.2015.7438307
  14. V. Dewanto, Aprinaldi, Z. Ian, and W. Jatmiko, “A novel knowledge-compatibility benchmarker for semantic segmentation,” International Journal on Smart Sensing and Intelligent Systems, vol. 8, no. 2,pp. 1284–1312, 2015.
  15. S. Isa, M. Suryana, M. Akbar, A. Noviyanto, W. Jatmiko, and A. Arymurthy, “Performance analysis of ecg signal compression using spiht,” International Journal on Smart Sensing and Intelligent Systems, vol. 6, no. 5, pp. 2011–2039, 2013.
  16. M. Campana and A. Sarti, “Cell morphodynamics visualization from images of zebrafish embryogenesis,” Computerized Medical Imaging and Graphics, vol. 34, no. 5, pp. 394 – 403, 2010. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S089561111000014510.1016/j.compmedimag.2010.01.00320171844
  17. C. Akinlar and C. Topal, “Edpf: A real-time parameter-free edge segment detector with a false detection control,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 26, no. 01,p. 1255002, 2012.
  18. C. Topal and C. Akinlar, “Edge drawing: A combined real-time edge and segment detector,” Journal of Visual Communication and Image Representation, vol. 23, no. 6, pp. 862 – 872, 2012. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S104732031200083110.1016/j.jvcir.2012.05.004
  19. C. Akinlar and C. Topal, “Edlines: A real-time line segment detector with a false detection control,” Pattern Recognition Letters, vol. 32, no. 13, pp. 1633 – 1642, 2011.
  20. A. Desolneux, L. Moisan, and J.-M. Morel, From Gestalt Theory to Image Analysis: A Probabilistic Approach, 1st ed. Springer Publishing Company, Incorporated, 2007.10.1007/978-0-387-74378-3
  21. 21 , “Meaningful alignments,” International Journal of Computer Vision, vol. 40, no. 1, pp. 7–23, 2000.10.1023/A:1026593302236
  22. R. Grompone von Gioi, J. Jakubowicz, J.-M. Morel, and G. Randall, “Lsd: a line segment detector,” Image Processing On Line, vol. 2, pp. 35–55, 2012.10.5201/ipol.2012.gjmr-lsd
  23. 23M. Fornaciari, A. Prati, and R. Cucchiara, “A fast and effective ellipse detector for embedded vision applications,” Pattern Recognition, vol. 47, no. 11, pp. 3693 – 3708, 2014.
Language: English
Page range: 1384 - 1409
Submitted on: Mar 31, 2016
Accepted on: Jul 21, 2016
Published on: Sep 1, 2016
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2016 Arie Rachmad Syulistyo, Aprinaldi,, Anom Bowolaksono, Budi Wiweko, Andrea Prati, Dwi M. J. Purnomo, Wisnu Jatmiko, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.