This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Methods for Fine Registration of Cadastre Graphs to Images
November 2007 (vol. 29 no. 11)
pp. 1990-2000
We propose two algorithms to match edges in a geometrically-imprecise graph to geometrically-precise strong boundaries in an image, where the graph is meant to give an a priori partition of the image into objects. This can be used to partition an image into objects described by imprecise external data, and thus to simplify the segmentation problem. We apply them to the problem of registering cadastre data to georeferenced aerial images, thus correcting the lack of geometrical detail of the cadastre data, and the fact that cadastre data gives information of a different nature than that found in images -- fiscal information as opposed to actual land use.

[1] J.-M. Viglino and L. Guigues, “Géoréférencement Automatique de Feuilles Cadastrales,” Proc. 13th Congrès de Reconnaissance de Formes et Intelligence Artificielle, pp. 135-143, Jan. 2002.
[2] P. Cachier, E. Bardinet, D. Dormont, X. Pennec, and N. Ayache, “Iconic Feature-Based Nonrigid Registration: The PASHA Algorithm,” Computer Vision and Image Understanding, vol. 89, nos. 2-3, pp. 272-298, Feb.-Mar. 2003.
[3] A. Goshtasby, L. Staib, C. Studholme, and D. Terzopoulos, “Nonrigid Image Registration: Guest Editors' Introduction,” Computer Vision and Image Understanding, vol. 89, nos. 2-3, pp.109-113, Feb.-Mar. 2003.
[4] H. Chui and A. Rangarajan, “A New Point Matching Algorithm for Nonrigid Registration,” Computer Vision and Image Understanding, vol. 89, nos. 2-3, pp. 114-141, Feb.-Mar. 2003.
[5] C. Hivernat and X. Descombes, “Mise en Correspondance et Recalage de Graphes: Application aux Réseaux Routiers Extraits d'un Couple Carte/Image,” Technical Report RR-3529, Institut Nat'l de Récherche en Informatique et en Automatique (INRIA), http:/www.inria.fr, Oct. 1998.
[6] S. Gautama and A. Borghgraef, “Using Graph Matching to Compare VHR Satellite Images with GIS Data,” Proc. IEEE Int'l Geoscience and Remote Sensing Symp., July 2003.
[7] V. Walter, “Automatic Classification of Remote Sensing Data for GIS Database Revision,” Int'l Archives of Photogrammetry and Remote Sensing (IAPRS), vol. 32, pp. 641-648, 1998.
[8] O.D. Faugeras and K.E. Price, “Semantic Description of Aerial Images Using Stochastic Labeling,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 3, no. 6, pp. 633-642, Nov. 1981.
[9] R.C. Wilson and E.R. Hancock, “Structural Matching by Discrete Relaxation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 6, pp. 634-648, June 1997.
[10] M. Gori, M. Maggini, and L. Sarti, “Exact and Approximate Graph Matching Using Random Walks,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 7, pp. 1100-1111, July 2005.
[11] R. Trias-Sanz, “An Edge-Based Method for Registering a Graph onto an Image with Application to Cadastre Registration,” Proc. Conf. Advanced Concepts for Intelligent Vision Systems, pp. 333-340, 2004.
[12] R. Trias-Sanz and M. Pierrot-Deseilligny, “A Region-Based Method for Graph to Image Registration with Application to Cadastre Data,” Proc. IEEE Int'l Conf. Image Processing, Oct. 2004.
[13] D. Marr, Vision. Freeman and Co., 1982.
[14] L. Guigues, H. Le Men, and J.-P. Cocquerez, “Scale-Sets Image Analysis,” Proc. IEEE Int'l Conf. Image Processing, Sept. 2003.
[15] S. Kirkpatrick, C. Gelatt, and M. Vecchi, “Optimization by Simulated Annealing,” Science, vol. 220, pp. 671-680, 1983.
[16] E. Dijkstra, “A Note on Two Problems in Connection with Graphs,” Numerical Math., vol. 1, pp. 269-271, 1959.
[17] D. Jungnickel, Graphs, Networks and Algorithms, series algorithms and computation in math., vol. 5. Springer, 1999.
[18] T. Law, H. Itoh, and H. Seki, “Image Filtering, Edge Detection, and Edge Tracing Using Fuzzy Reasoning,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 5, pp. 481-491, May 1996.
[19] A. Rosenfeld, R. Hummel, and S. Zucker, “Scene Labeling by Relaxation Operations,” IEEE Trans. Systems, Man, and Cybernetics, vol. 6, pp. 320-433, June 1976.
[20] A.M.N. Fu and H. Yan, “A New Probabilistic Relaxation Method Based on Probability Space Partition,” Pattern Recognition, vol. 30, no. 11, pp. 1905-1917, 1997.
[21] S.W. Zucker, E.V. Krishnamurthy, and R.L. Haar, “Relaxation Processes for Scene Labeling: Convergence, Speed and Stability,” IEEE Trans. Systems, Man, and Cybernetics, vol. 8, pp. 41-48, 1978.
[22] Q. Chen and J.Y.S. Luh, “Ambiguity Reduction by Relaxation Labeling,” Pattern Recognition, vol. 27, pp. 165-180, 1994.
[23] Q. Chen and J.Y.S. Luh, “Relaxation Labeling Algorithm for Information Integration and Its Convergence,” Pattern Recognition, vol. 28, pp. 1705-1722, 1995.

Index Terms:
Remote sensing, registration, graph labeling, stochastic methods, cartography
Citation:
Roger Trias-Sanz, Marc Pierrot-Deseilligny, Jean Louchet, Georges Stamon, "Methods for Fine Registration of Cadastre Graphs to Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 11, pp. 1990-2000, Nov. 2007, doi:10.1109/TPAMI.2007.1108
Usage of this product signifies your acceptance of the Terms of Use.