References



No, I didn't use all of these references ! Most of this project was inspired by Atallah. Anyway, here is a listing of everything I found, as of Oct. 98, about algorithms on Hausdorff distance and image matching. Hope you can find some good material for yourself.


  1. H. Alt (1994). Matching shapes with a reference point. Technical report B 94-18, Institut für Informatik, Freie Universität Berlin, DE.

  2. H. Alt, B. Behrends, J. Blömer (1992). Approximate matching of polygonal shapes. Technical report B 93-10, Institut für Informatik, Freie Universität Berlin, DE. 16 pages.

  3. M. J. Atallah (1983). A linear time algorithm for the Hausdorff distance between convex polygons. Information Processing Letters, v. 17, pp. 207-209.

  4. M. Beauchemin, K. P. B. Thomson, G. Edwards (1998). On the Hausdorff distance used for the evaluation of segmentation results. Canadian Journal of Remote Sensing, v. 24(1), pp. 3-8. Also appeared in Proc. Int. Symp. on Geomatics in the Era of Radarsat (GER'97, Ottawa, CA).

  5. E. Belogay, C. Cabrelli, U. Molter, R. Shonkwiler (1997). Calculating the Hausdorff distance between curves. Information Processing Letters, v. 64, pp. 17-22.

  6. I. Bloch (1996). Fuzzy geodesic distance in images. In T. Martin and A. Ralescu (ed.), Lecture Notes In Artificial Intelligence v. 1188 : Fuzzy Logic in Artificial Intelligence, towards Intelligent Systems, Springer, pp. 153-166.

  7. L. P. Chew, K. Kedem (1998). Getting around a lower bound for the minimum Hausdorff distance. Computational Geometry, Theory and Applications, v. 10(3), pp. 197-202.

  8. L. P. Chew, K. Kedem, S. Schirra (1994). On characteristic points and approximate decision algorithms for the minimum Hausdorff distance. Technical report MPI-I-94-150, Max-Planck-Institut für Informatik, Saarbrücken, DE. 10 pages.

  9. M. P. Dubuisson, A. K. Jain (1994). Modified Hausdorff distance for object matching. Proc. of IAPR Int. Conf. on Pattern Recognition (ICPR'94, Jerusalem, IS), v. A, pp. 566-568.

  10. P. W. Goldberg (1993). PAC-learning geometrical figures. Ph.D. thesis, Lab. for foundations of computer science, University of Edinburgh, UK.

  11. W. E. Grimson, D. P. Huttenlocher (1994). Analyzing the probability of a false alarm for the Hausdorff distance under translation. Proc. of Image Understanding Workshop (ARPA'94, Monterey, CA), v. II, pp. 1257-1262.

  12. D. P Huttenlocher, G. A. Klanderman, W. J. Rucklidge (1993). Comparing images using the Hausdorff distance. IEEE Trans. on Pattern Analysis and Machine Intelligence, 15(9), pp. 850-863. Also appeared in CVPR'92, pp. 654-656, under Comparing images using the Hausdorff distance under translation.

  13. D. P. Huttenlocher, K. Kedem (1990). Computing the minimum Hausdorff distance for point sets under translation. Proc. of 6th Annual ACM Symp. on Comp. Geom. (SCG'90, Berkeley, CA), pp. 340-349.

  14. D. P. Huttenlocher, K. Kedem, J. M. Kleinberg (1992). On dynamic Voronoi diagrams and the minimum Hausdorff distance for point sets under Euclidian motion in the plane. Proc. of 8th Annual ACM Symp. on Comp. Geom. (SCG'92, Berlin, DE), pp. 110-119. Also known as tech. report TR 92-1271, Dept. of computer science, Cornell University, NY.

  15. D. P. Huttenlocher, R. H. Lilien, C. F. Olson (1996). Approximate Hausdorff matching using Eigenspaces. Proc. of Image Understanding Workshop (ARPA'96, Palm Springs, CA), pp. 1181-1186. Also appeared in Proc. of European Conf. on Computer Vision, pp. 536-545 (1996).

  16. D. P. Huttenlocher, W. J. Rucklidge (1992). A multi-resolution technique for comparing images using the Hausdorff distance. Tech. report TR 92-1321, Dept. of Computer science, Cornell University, NY. 20 pages. Also appeared in PAMI, v. 15 (1993), and in Proc. of CVPR'93.

  17. K. Kedem, Y. Yarmovski (1996). Curve based stereo matching using the minimum Hausdorff distance. Proc. of 12th Annual ACM Symp. on Comp. Geom. (SCG'96, Philadelphia, PA), pp. 415-418.

  18. C. F. Olson (1998). Probabilistic formulation for Hausdorff matching. Proc. of IEEE Conf. on Vision and Pattern Recognition (CVPR'98, Santa Barbara, CA), pp. 150-156.

  19. J. Paumard, E. Aubourg (1997). Adjusting astronomical images using a censored Hausdorff distance. Proc. of 4th IEEE Int. Conf. on Image Processing (ICIP '97, Santa Barbara, CA), v. III, pp. 232-xxx.

  20. F. P. Preparata, M. I. Shamos (1985). Computational geometry, an introduction. Springer-Verlag, NY. 398 pages.

  21. G. Rote (1991). Computing the minimum Hausdorff distance between two point sets on a line under translation. Information Processing Letters, v. 38, pp. 123-127.

  22. W. Rucklidge (1995). Lower bounds for the complexity of Hausdorff distance. Tech. report TR 94-1441, Dept. of computer science, Cornell University, NY. A similar title appeared in Proc. 5th Canad. Conf. on Comp. Geom. (CCCG'93, Waterloo, CA), pp. 145-150.

  23. W. Rucklidge (1995). Efficient computation of the minimum Hausdorff distance for visual recognition. Ph.D. thesis, Dept. of computer science, Cornell University, NY.

  24. W. J. Rucklidge (1995). Locating objects using the Hausdorff distance. Proc. of 5th Int. Conf. on Computer Vision (ICCV'95, Cambridge, MA), pp. 457-464.

  25. W. J. Rucklidge (1996). Efficient visual recognition using the Hausdorff distance. Lecture Notes in Computer Science, no 1173, Springer-Verlag, NY.

  26. W. J. Rucklidge (1997). Efficiently locating objects using the Hausdorff distance. Int. J. of Computer Vision, 24(3), pp. 251-270.

  27. R. Shonkwiler (1989). An image algorithm for computing the Hausdorff distance efficiently in linear time. Information Processing Letters, v. 30, pp. 87-89.

  28. R. Shonkwiler (1991). Computing the Hausdorff set distance in linear time for any Lp point distance. Information Processing Letters, v. 38, pp. 201-207.

  29. J. H. Yi, B. Bhanu, M. Li (1996). Target indexing in SAR images using scattering centers and the Hausdorff distance. Pattern Recognition Letters, v. 17(11), pp. 1191-1198

  30. X. Yi, O. C. Camps (1995). Line feature-based recognition using the Hausdorff distance. Proc. of IEEE Symp. on Computer Vision (SCV'95, Miami Beach, FL), pp. 79-84.

  31. X. Yi, O. C. Camps (1997). Robust occluding contour detection using the Hausdorff distance. Proc. of IEEE Conf. on Vision and Pattern Recognition (CVPR'97, San Juan, PR), pp. 962-967.