Shape matching of partially occluded curves invariant under projective transformation

Computer Vision and Image Understanding

Volumn 93, Issue 1, 2004, Pages 34-64

  Orrite, Carlos ^a   Elias Herrero, J ^a  

^a UNIVERSITY OF ZARAGOZA   (Spain)

Author keywords

Affine transformation; Alignment approach; Bitangency; Computer vision; Hausdorff distance; Object recognition; Shape matching

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; IMAGE ANALYSIS; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; MATRIX ALGEBRA; OBJECT RECOGNITION; PATTERN MATCHING;

AFFINE TRANSFORMATION; ALIGNMENT APPROACH; BITANGENCY; HAUSDORFF DISTANCES; SHAPE MATCHING;

COMPUTER VISION;

EID: 0347947003     PISSN: 10773142     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cviu.2003.09.005     Document Type: Article

References (29)

1. D.W. Murray, Strategies in object recognition, Gec J. Res. 6 (2) (1988) 80-95.
2. Y. Gdalyahu, D. Weinshall, Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes, IEEE Trans. Pattern Anal. Machine Intell. 21 (12) (1999) 1312-1328.
3. S. Ullman, Aligning pictorial descriptions: an approach to object recognition, Cognition 32 (1989) 193-254.
4. N. Ayache, O.D. Faugeras, HYPER: a new approach for the recognition and positioning of two-dimensional objects, IEEE Trans. Pattern Anal. Machine Intell. PAMI-8 (1) (1986) 44-54.
5. A. Zisserman, D.A. Forsyth, J.L. Mundy, C.A. Rothwell, Recognizing general curved objects efficiently, in: Geometric Invariance in Computer Vision, MIT Press, Cambridge, MA, 1992, pp. 228-251.
6. D.P. Huttenlocher, S. Ullman, Object Recognition using alignment, MIT AI Memo 937.
7. Z. Xue, D. Shen, E.K. Teoh, An efficient fuzzy algorithm for aligning shapes under affine transformations, Pattern Recognition 34 (2001) 1171-1180.
8. H. Nishida, Model-based shape matching with structural feature grouping, IEEE Trans. Pattern Anal. Machine Intell. 17 (3) (1992) 315-320.
9. M. Singh, A. Chatterjee, S. Chaudhury, Matching structural shape descriptions using genetic algorithms, Pattern Recognition 30 (9) (1997) 1451-1462.
10. P.W. Huang, S.K. Dai, P.L. Lin, Planar shape recognition by directional flow-change method, Pattern Recognition Lett. 20 (1999) 163-170.
11. K. Siddiqi, A. Shokoufandeh, S.J. Dickinson, S.W. Zucker, Shock graphs and shape matching, Internat. J. Comput. Vision 35 (1) (1999) 13-32.
12. I. Biederman, Recognition-by-components: a theory of human image understanding, Psychol. Rev. 94 (2) (1987) 115-147.
13. K. Siddiqi, B.B. Kimia, Parts of visual form: computational aspects, IEEE Trans. Pattern Anal. Machine Intell. 17 (3) (1995) 239-251.
14. D.G. Lowe, Organisation of smooth image curves at multiple scales, Internat. J. Comput. Vision 3 (1989) 119-130.
15. F. Mokhtarian, A.K. Mackworth, A theory of multiscale-based shape representation for planar curves, IEEE Trans. Pattern Anal. Machine Intell. 14 (1992) 789-805.
16. H. Asada, M. Brady, The curvature primal sketch, IEEE Trans. Pattern Anal. Machine Intell. 8 (1986) 2-14.
17. P. Saint-Marc, G. Medioni, Adaptive smoothing for feature extraction, in: Proc. DARPA Image Understanding Workshop, Boston, MA, 1988, pp. 1100-1113.
18. C.H. Teh, R.T Chin, On the detection of dominant points on digital curves, IEEE Trans. Pattern Anal. Machine Intell. 11 (1989) 859-872.
19. C. Orrite, A. Alcolea, Identifying perceptually salient segments on planar curves, Pattern recognition and image analysis, Preprints of the VII National Symposium on Pattern Recognition and Image Analysis, 1997, pp. 419-424.
20. M.A. Fischler, H.C. Wolf, Locating perceptually salient points on planar curves, IEEE Trans. Pattern Anal. Machine Intell. 16 (1994) 113-129.
21. D.P. Huttenlocher, G.A. Klanderman, W.J. Rucklidge, Comparing images using the Hausdorff distance, IEEE Trans. Pattern Anal. Machine Intell. 15 (9) (1993) 850-863.
22. W.J. Rucklidge, Efficiently locating objects using the Hausdorff distance, Internat. J. Comput. Vision 24 (3) (1997) 251-270.
23. D.-G. Sim, R.-H. Park, Two-dimensional object alignment based on the robust oriented Hausdorff similarity measure, IEEE Trans. Pattern Anal. Machine Intell. 10 (3) (2001) 475-483.
24. C. Orrite, A. Alcolea, A. Campo, Recognition of partially occluded flat objects, in: Lectures Notes in Artificial Intelligence, vol. 1484, Springer, Berlin, 1998, pp. 242-252.
25. P.K. Ser, C.S.T. Choy, W.C. Siu, Genetic algorithm for the extraction of nonanalytic objects from multiple dimensional parameter space, Comput. Vision Image Understanding 73 (1) (1999) 1-13.
26. X.X. Yi, O.I. Camps, Line-based recognition using a multidimensional Hausdorff distance, IEEE Trans. Pattern Anal. Machine Intell. 21 (9) (1999) 901-916.
27. M. Sonka, V. Hlavac, R. Boyle, Image Processing, Analysis and Machine Vision, second ed., Thomson Publishing, 1998.
28. P.J. Besl, N.D. McKay, A method for registration of 3-D shapes, IEEE Trans. Pattern Anal. Machine Intell. 14 (2) (1992) 239-256.
29. J. Feldmar, N. Ayache, F. Betting, 3D-2D projective registration of free-form curves and surfaces, Comput. Vision Image Understanding 65 (3) (1997) 403-424.