eprintid: 539
rev_number: 6
eprint_status: archive
userid: 5
dir: disk0/00/00/05/39
datestamp: 2011-03-28
lastmod: 2013-07-01 11:39:04
status_changed: 2013-07-01 11:39:04
type: techreport
metadata_visibility: show
item_issues_count: 0
creators_name: Dao, S.M.
creators_name: De Natale, Francesco
creators_name: Massa, Andrea
title: Edge Potential Functions (EPF) and Genetic Algorithms (GA) for Edge-Based Matching of Visual Objects
ispublished: pub
subjects: TU
full_text_status: public
abstract: Edges are known to be a semantically rich representation of the contents of a digital image. Nevertheless, their use in practical applications is sometimes limited by computation and complexity constraints. In this paper, a new approach is presented that addresses the problem of matching visual objects in digital images by combining the concept of Edge Potential Functions (EPF) with a powerful matching tool based on Genetic Algorithms (GA). EPFs can be easily calculated starting from an edge map and provide a kind of attractive pattern for a matching contour, which is conveniently exploited by GAs. Several tests were performed in the framework of different image matching applications. The results achieved clearly outline the potential of the proposed method as compared to state of the art methodologies. (c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
date: 2007-01
date_type: published
institution: University of Trento
department: informaticat
refereed: TRUE
referencetext: [1] R.C. Veltkamp and M. Hagedoorn, "State-of-the-Art in Shape Matching"; Principles of visual information retrieval, Springer-Verlag, London, UK, ISBN:1-85233-381-2, pp. 87-119, 2000. 
[2] V.N. Gudivada, and V.V. Raghavan, "Content-Based Image Retrieval Systems"; Computer, Vol. 28, No. 9, pp. 18-21, Sept. 1995. 
[3] S.F. Chang, "Content-Based Indexing and Retrieval of Visual Information"; IEEE Signal Processing Magazine, pp. 45-48, July 1997. 
[4] A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, R. Jain: "Content-based image Retrieval at the End of the Early Years"IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No.12, pp. 1349-1380, Dec. 2000. 
[5] I. Biederman, "Human image understanding: Recent research and a theory", Computer Vision, Graphics, and Image Processing, vol. 32, pp. 29-73, 1985. 
[6] M.I. Posner"Foundations of cognitive Science"; Editor MIT Press, ISBN: 0262161125, 1989. 
[7] G. Borgefors, "Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm", IEEE Trans. on Pattern Analysis and Matching Intelligence, Vol. 10, No. 6, pp. 849-865, Nov. 1988. 
[8] S. Loncaric, "A Survey of Shape Analysis Techniques"; Pattern Recognition, vol.  31, no. 8, pp. 983-1001, 1998. 
[9] D. G. Kendall, D. Barden, T.K. Carne, and H. Le, Shape and Shape Theory. Wiley, Chichester, England, 1999. 
[10] F.L. Bookstein, "Size and shape spaces for landmark data in two dimensions"; Statistical Science, vol. 1, no. 2, pp. 181-242, 1986. 
[11] I. Dryden and K. Mardia, Statistical Shape Analysis. New York: Wiley, 1998.  
[12] I. Dryden, "Statistical shape analysis in high-level vision";, in Proc. of IMA workshop on Image Analysis and High Level Vision Modelling, 2000. 
[13] T. Cootes, C. Taylor, D. Cooper, and J. Graham, "Active shape models – their training and application"; Computer Vision and Image Understanding, vol. 61, no. 1, pp. 38-59, 1995. 
[14] T.K. Carne, "The geometry of shape spaces"; Proc. of the London Mathematic Society, vol. 3, no. 61, pp. 407-432, 1990. 
[15] C.G. Small, The Statistical Theory of Shape, Springer, 1996. 
[16] N. Naswani, A.R. Chowdhury, and E. Chellappa, "Statistical Shape Theory for Activity Modelling"In Proc. of ICASSP 03. 
[17] U. Grenander, General Pattern Theory, Oxford University Press, England, 1993. 
[18] A. Srivastava, S.H. Joshi, W. Mio, and X. Liu, "Statistical Shape Analysis: Clustering, Learning, and Testing"; IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 27, no. 4, April 2005. 
[19] F. Mokhtarian, "Silhouette-Based Isolated Object Recognition through Curvature Scale Space"; IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 17, no. 5, pp. 539-544, May 1995. 
[20] P.W.M. Tsang, "Enhancement of a Genetic Algorithm for Affine Invariant planar Object Shape Matching Using the Migrant Principle"; IEEE Image and Signal Processing, vol. 150, no. 2, pp. 107-113, 2003. 
[21] G. L. Scott and H. C. Longuet-Higgins, "An Algorithm for Associating the Features of Two Patterns," Proc.of the Royal Society B, B244, pp. 21-26, 1991. 
[22] Y. Xu, E. Saber, and A.M. Tekalp, "Image Retrieval through Shape Matching of Partially Occluded Objects Using Hierarchical Content Description"; Proc. International Conference on Image Processing, pp. 73-76, 2000. 
[23] J.R. Beveridge, H. Weiss, E.M. Riseman, "Combinatorial Optimization Applied to Variable Scale 2D Model Matching"; Proc. 10th International Conference on IEEE Pattern Recognition, pp. 18-23, 1990. 
[24] T. Kawaguchi, R.I. Nagata, and T. Sinozaki, "Detection of Target Models in 2D Images by Line-Based Matching and a Genetic Algorithm"; Proc. International Conf. on IEEE Image Processing, vol. 2, pp. 710-714, 1999.   
[25] T. Kawaguchi and M. Nagao, "Recognition of Occluded Objects by a Genetic Algorithm"Proc. 14th International Conf. on IEEE Pattern Recognition, vol.1, pp. 233-237, 1998. 
[26] H.G. Barrow, J.M. Tenenbaum, R.C. Bolles, and H.C Wolf, "Parametric correspondence and Chamfer matching: Two new techniques for image matching", Proc. 5th Int. Joint Conf. Artificial Intelligence, Cambridge, MA, pp. 659-663, 1977. 
[27] E. Akleman and J. Chen, "Generalized Distance Functions"; Proc. Shape Modeling International Conf. on Shape Modeling and Applications, pp. 72-79, 1999. 
[28] G. Borgefors, "Distance transformations in Digital Image"; Computer Vision, Graphics, and Image Processing, vol.34, pp. 344-371, 1986. 
[29] D.P. Huttenlocher, G.A. Klanderman, and W.J. Rucklidge, "Comparing Images Using the Hausdorff Distance"; IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.15, no.9, pp. 850-863, Sep. 1993. 
[30] D.P. Huttenlocher and W.J. Rucklidge, "A Multi-Resolution Technique for Comparing Images Using the Hausdorff Distance"; Proc. International Symposium on Computer Vision, pp. 705-706, 1993. 
[31] C.F. Olson and D.P. Huttenlocher, "Recognition by Matching Dense, Oriented Edge Pixels"; Proc. International Symposium on Computer Vision, pp. 91-96, 1995 
[32] C.F. Olson and D.P. Huttenlocher, "Automatic Target Recognition by Matching Oriented Edge Pixels"; IEEE Trans. on Image Processing, vol.6, no.1, pp. 103-113, January 1997. 
[33] D.G. Sim and R.H. Park, "Two-Dimensional Object Alignment Based on the Robust Oriented Hausdorff Similarity Measure"; IEEE Trans. on Image Processing, Vol. 10, No. 2, pp. 475-483, 2001. 
[34] B. Li, Q. Meng, and H. Holstein, "Point Pattern Matching and Applications – a Review"; IEEE, vol., no., pp. 729-736, 2003. 
[35] J. Wang, K.W. Bowyer, T.A. Sanocki, and S. Sarkar, "The Effect of Edge Strength on Object Recognition from Edge Images"; Proc. International Conference on Image (ICIP 98), pp. 45-49, 1998. 
[36] M.I. Chowdhury and J.A. Robinson, "Improving image segmentation using edge information"; Proc. Conference on Electrical and Computer Engineering, vol. 1, pp. 312-316, 2000. 
[37] W.Y. Ma and B.S. Manjunath, "EdgeFlow: A Technique for Boundary Detection and Image Segmentation"; IEEE Trans. in Image Processing, vol. 9, no. 8, pp. 1375-1388, 2000 
[38] C.F. Olson, "Maximum-Likelihood Image Matching"; IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 853-857, 2002. 
[39] O. Khatib, "Real-time Obstacle Avoidance for Manipulators and Mobile Robots"; The International Journal of Robotics Research, vol. 5, no. 1, pp. 90-98, 1986. 
[40] J.A. Stratton, Electromagnetic Theory. McGraw-Hill Book, NY 1941. 
[41] G. Oller, P. Marthon, and L. Denise, "SAR image matching using the edge strength map"; Proc. IEEE International Conference on Geoscience and Remote Sensing Symposium (IGARSS '02), vol. 4 , pp. 2495-2497, 2002. 
[42] J.H. Holland, "Adaptation in Natural and Artificial Systems",Univ. Michigan Press, Ann Arbor, 1975. 
[43] K.A. De Jong, "An analysis of the behavior of a class of genetic adaptive systems"; Ph. D. Dissertation, Univ. Michigan, 1975. 
[44] D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Weiley., 1989. 
[45] J. Inglada and F. Adragna, "Automatic multi-sensor image registration by edge matching using genetic algorithms"; Proceedings of International Conference on Geoscience and Remote Sensing Symposium (IGARSS'01), vol. 5, pp. 2313-2315, 2001 
[46] J.M. Johnson and Y.R. Samii, "Genetic Algorithms in engineering electromagnetics"; IEEE Trans. on Antennas and Progat. Magazine, vol. 39, no. 4, pp. 7-25, August 1997. 
[47] M. Pastorino, A. Massa and S. Caorsi, "A microwave inverse scattering technique for image reconstruction based on a genetic algorithm," IEEE Transactions on Instrumentation and Measurement, vol. 49, no. 3, pp. 573-578, June 2000. 
[48] Y.K., Wang and K.C. Fan, "Applying Genetic Algorithm on Pattern Recognition: An Analysis and Survey"; Proceedings of  ICPR'96, pp. 740-744. 1996.   
[49] L. Zhang, W. Xu, and C. Chang, "Genetic algorithm for affine point pattern matching"; Pattern Recognition Letters, vol. 24, pp. 9-19, 2003. 
[50] P.Y. Yin, "A new circle/ellipse detector using genetic algorithms"; Pattern Recognition Letters, vol. 20, pp. 731-740, 1999.
citation:   Dao, S.M. and De Natale, Francesco and Massa, Andrea  (2007) Edge Potential Functions (EPF) and Genetic Algorithms (GA) for Edge-Based Matching of Visual Objects.  [Technical Report]     
document_url: http://www.eledia.org/students-reports/539/1/DISI-11-077.R108.pdf