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SUBSIDENCE TROUGHS DETECTION FOR SAR IMAGES - PRELIMINARY RESULTS

Justyna Bala, Stanislawa Porzycka - Strzelczyk, Jacek Strzelczyk

First published: 2015https://doi.org/10.5593/sgem2015/b21/s8.106View metrics

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Title
SUBSIDENCE TROUGHS DETECTION FOR SAR IMAGES - PRELIMINARY RESULTS
Authors
Justyna Bala, Stanislawa Porzycka - Strzelczyk, Jacek Strzelczyk
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 15th International Multidisciplinary Scientific GeoConference SGEM2015, INFORMATICS, GEOINFORMATICS AND REMOTE SENSING
Publisher
Stef92 Technology
Year
2015
Pages
829-836
ISSN
1314-2704
ISBN
978-619-7105-34-6
Language
en
Publication type
Conference Paper
References20
  1. S. Porzycka, J. Strzelczyk, Preliminary results of ground deformations monitoring within mining area of “Prosper -Haniel” coal mine, SGEM 2012, conference proceedings. Vol. 2, pp. 895– 899 ;

  2. Suzuki, S. and Abe, K., Topological Structural Analysis of Digitized Binary Images by Border Following. CVGIP 30 1, 1985, pp 32-46; International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org 15th International Multidisciplinary Scientific GeoConferences SGEM2015

  3. Andrew W. Fitzgibbon, R.B.Fisher. A Buyer’s Guide to Conic Fitting. Proc.5th British Machine Vision Conference, Birmingham, 1995, pp. 513-522;

  4. Golub G.H., Loan C.F.;Matrix Computations, 1989, Johns Hopkins, Second edition;

  5. R. Duda and P. Hart, Use of the hough transformation to detect lines and curves in pictures, Communications of the ACM, , 1972, vol. 15, no. 1, pp. 11–15;

  6. L. Xu, E. Oja, and P. Kultanen, A new curve detection method: randomized hough transform (rht), Pattern Recognition Letters, 1990, vol. 11,no. 5, pp. 331 – 338;

  7. J. Yao, N. Kharma, and P. Grogono, “A multi-population genetic algorithm for robust and fast ellipse detection, Pattern Analysis and Application, 2005, vol. 8, no. 1, pp. 149–162;

  8. F. Mai, Y. Hung, H. Zhong, and W. Sze, “A hierarchical approach forfast and robust ellipse extraction, Pattern Recognition, 2008, vol. 41, no. 8,pp. 2512 – 2524;

  9. E. Kim, M. Haseyama, and H. Kitajima, “Fast and robust ellipse extrac -tion from complicated images,” inProceedings of IEEE InternationalConference on Information Technology and Applications, 2002, pp. 357– 362.

  10. Lei Huang, Jinwen Ma, A Probabilistic Mixture Approach to Automatic Ellipse Detection, Proceedings of the international conference on image processing, computer & pattern recognition, 2013, vol II, pp 573. International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org

  11. S. Porzycka, J. Strzelczyk, Preliminary results of ground deformations monitoring within mining area of “Prosper -Haniel” coal mine, SGEM 2012, conference proceedings. Vol. 2, pp. 895– 899 ;

  12. Suzuki, S. and Abe, K., Topological Structural Analysis of Digitized Binary Images by Border Following. CVGIP 30 1, 1985, pp 32-46; International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org 15th International Multidisciplinary Scientific GeoConferences SGEM2015

  13. Andrew W. Fitzgibbon, R.B.Fisher. A Buyer’s Guide to Conic Fitting. Proc.5th British Machine Vision Conference, Birmingham, 1995, pp. 513-522;

  14. Golub G.H., Loan C.F.;Matrix Computations, 1989, Johns Hopkins, Second edition;

  15. R. Duda and P. Hart, Use of the hough transformation to detect lines and curves in pictures, Communications of the ACM, , 1972, vol. 15, no. 1, pp. 11–15;

  16. L. Xu, E. Oja, and P. Kultanen, A new curve detection method: randomized hough transform (rht), Pattern Recognition Letters, 1990, vol. 11,no. 5, pp. 331 – 338;

  17. J. Yao, N. Kharma, and P. Grogono, “A multi-population genetic algorithm for robust and fast ellipse detection, Pattern Analysis and Application, 2005, vol. 8, no. 1, pp. 149–162;

  18. F. Mai, Y. Hung, H. Zhong, and W. Sze, “A hierarchical approach forfast and robust ellipse extraction, Pattern Recognition, 2008, vol. 41, no. 8,pp. 2512 – 2524;

  19. E. Kim, M. Haseyama, and H. Kitajima, “Fast and robust ellipse extrac -tion from complicated images,” inProceedings of IEEE InternationalConference on Information Technology and Applications, 2002, pp. 357– 362.

  20. Lei Huang, Jinwen Ma, A Probabilistic Mixture Approach to Automatic Ellipse Detection, Proceedings of the international conference on image processing, computer & pattern recognition, 2013, vol II, pp 573. International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org

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