An extension of the generalized hough transform to realize affine-invariant two-dimensional(2D) shape detection

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 65-69

  Kimura, Akio ^a   Watanabe, Takashi ^a  

^a IWATE UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

AFFINE-INVARIANT; OVERLAPPING OBJECTS; SHAPE BOUNDARY; SHAPE DETECTION; AFFINE INVARIANT; AFFINE TRANSFORMATIONS; DIRECT COMPUTATIONS; FUNDAMENTAL RESEARCH; GENERALIZED HOUGH TRANSFORM; SHAPE BOUNDARIES; TWO DIMENSIONAL (2 D);

COMPUTATION THEORY; COMPUTER VISION; IMAGE PROCESSING; MATHEMATICAL MODELS; PATTERN RECOGNITION; PROBLEM SOLVING; HOUGH TRANSFORMS;

HOUGH TRANSFORMS; AFFINE TRANSFORMS;

EID: 33747618159     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (23)

1. D.H.Ballard. Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition, 13(2):111-122, 1981.
2. Y.Lamdan, J.T.Schwartz, and H.J.Wolfson. Affine invariant model-based object recognition. IEEE Trans. Rob. Aut., 6:578-589, 1990.
3. M.S.Costa, R.M.Haralick, and L.G.Shapiro. Optimal affine-invariant matching: Performance characterization. SPIE. 1662:21-34, 1992.
4. F.C.D.Tsai, A probabilistic approach to geometric hashing using line features. Computer Vision and Image Understanding, 63(1): 182-195, 1996.
5. J. Ben-Arie and Z.Wang. Pictorial recognition of objects employing affine invariance in the frequency domain. IEEE Trans. Pattern Anal. & Mach. Intell., 20(6):604-618, 1998.
6. H.G.Feichtinger and T.Strohmer. Gahor Analysis and algorithms-theory and applications-. Birkhauser Verlag. 1997.
7. J.Matas, J.Burianek, and J.Kittler, Object recognition using the invariant pixel-set signature. Proc. of the British Machine Vision Conference. September 2000.
8. D.G.Lowe, Object recognition from local scale-invariant features. Proc. of the International Conference on Computer Vision. Corfu. 1150-1157, 2000.
9. Schmid C. and R.Mohr. Local grayvalue invariants for imase retrieval. IEEE Trans. Pattern Anal. & Mach. Intell., 19(5):530-534, 1997.
10. A.M.Bruckstein, R.J.Holt, A.Netravali, and T.J Richardson. Invariant signatures for planar shape recognition under partial occlusion. Computer Vision. Graphics and Image Processing. 58(1):49-65, 1993.
11. E.Calabi, P.J.Olver, C.Shakiban, A.Tannenbaum, and S.Haker. Differential and numerically invariant signature curves applied to object recognition. Int. Journal of Computer Vision. 26:107-135, 1998.
12. R.Berthilsson and A.Heyden. Recognition of planar objects using the density of affine-shape partial occlusion. Computer Vision. Graphics and Image Processing, 58(1)-49-65, 1993.
13. J.Subrahmonia, D.Cooper, and D.Keren. Practical reliable Bayesian recognition of 2D and 3D objects using implicit polynomials and algebraic invariants. IEEE Trans. Pattern Anal. & Mach. Intell., 18:505-519, 1996.
14. M.Werman and D.Weinshall. Similarity and affine invariant distances between 2D point sets. IEEE Trans. Pattern Anal. & Much. Intell. 17(8):810-814, 1995.
15. S.Startchik, R.Milanese, C.Rauber, and T.Pun. Planar shape databases with affine invariant search. Proc. of the International Workshop on Image Databases and Multi Media Search, August 1996.
16. D. Zhao and J. Chen. Affine curve moment invariants for shape recognition. Pattern Recognition, 30(6):895-901, 1997.
17. D.Shen, Horace H.S.Ip, and E.K.Teoh. Affine invariant detection of perceptually parallel 3D planar curves. Pattern Recognition. 33:1909-1918, 2000.
18. S.Y.Yuen and C.H.Ma, Genetic algorithm with competitive image labelling and least square. Pattern Recognition, 33:1949-1966, 2000.
19. G. Bebis, M.Georgiopoulos, N.V.Lobo, and M.Shah. Learning affine transformations. Pattern Recognition, 32(10):1783-1799, 1999.
20. M.I.Khalil and M.M.Bayoumi. A dyadic wavelet affine invariant function for 2D shape recognition. IEEE Trans. Pattern Anal. &Mach. lntell., 23(10):1152-1164, 2001.
21. T. Watanabe, M. Hatakeyama, and A. Kimura, Extraction of tangent information and detection of broken ellipses using hough transform. Trans. of the Institute of Electronics. Information and Communication Engineers, J82-D-11(12):2221-2229, December 1999, in Japanese
22. J.Illinzwoth and J. Kittler. The adaptive Hough transform. IEEE Trans. Pattern Anal. & Mach. Intell., 9(5):690-698, 1987.
23. J. Canny. A computational approach to edge detection. IEEE Trans. Pattern Anal. & Mach. Intell., 8(6):679-698, 1986.