An investigation of the nature of parameterization for the Hough transform

Pattern Recognition

Volumn 30, Issue 6, 1997, Pages 1009-1040

  Yuen, Shiu Yin ^a   Ma, Chi Ho ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Computer graphics; Fourier descriptor; Hough transform; Inherent bias; Parameterization; Parametric form; Search space; Subdivision method

Indexed keywords

ANALOG TO DIGITAL CONVERSION; COMPUTER GRAPHICS; FOURIER TRANSFORMS; PARAMETER ESTIMATION;

FOURIER PARAMETERIZATION; HOUGH TRANSFORM;

OBJECT RECOGNITION;

EID: 0031162487     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(97)85267-3     Document Type: Article

References (19)

1. P. V. C. Hough, Methods and means for recognising complex patterns, U.S. Patent No. 3069654 (1962).
2. C. M. Brown, Inherent bias and noise in the Hough transform, IEEE Trans. PAMI-5(5), 493-505 (1983).
3. R. O. Duda and P. E. Hart, Use of the Hough transform to detect lines and curves in pictures, Commun. ACM 15, 11-15 (1972).
4. W. C. Y Lam, S. Y. Yuen and D. N. K. Leung, Fourier parameterization provide uniform bounded Hough space, Lecture Notes in Computer Science, Vol. 719, D. Chetverikov and G. Kropatsch, eds, pp. 183-90. Springer, Berlin (1993).
5. J. Princen, J. Illingworth and J. Kittler, A formal definition of the Hough transform: properties and relationships, J. Math. Imaging Vision 1, 153-168 (1992).
6. Z. Hu and S. D. Ma, An inherent probabilistic aspect of the Hough transform, Lecture Notes in Computer Science, Vol. 1024, R. T. Chin et al., eds, pp. 505-506. Springer, Berlin (1995).
7. T. M. Van Veen and F. C. A. Groen, Discretization errors in the Hough transform, Pattern Recognition 14, 137-145 (1981).
8. W. C. Y. Lam, T. S. Lam, S. Y. Yuen and D. N. K. Leung, An analysis on quantizing the Hough space, Pattern Recognition Lett. 15, 1127-1135 (1994).
9. J. Sklansky, On the Hough technique for curve detection, IEEE Trans. Comput. C-27(10), 923-926 (1978).
10. D. Hearn and M. P. Baker, Computer Graphics, Prentice Hall, 2nd Edn (1994).
11. P. M. Merlin and D. J. Farber, A parallel mechanism for detecting curves in pictures, IEEE Trans. Comput. C-24, 96-98 (1975).
12. D. H. Ballard, Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognition 13, 111-122 (1981).
13. P. C. F. Lee, personal communications (1994).
14. C. S. Lin and C. L. Hwang, New forms of shape invariant from elliptic Fourier descriptors, Pattern Recognition 20(5), 535-545 (1987).
15. G. Gerig and F. Klein, Fast contour identification through efficient Hough transform and simplified interpretation strategy, Proc. 8th Int. Joint Conf. Pattern Recog., Paris, France, 498-500 (1986).
16. T. Risse, Hough transform for line recognition: Complexity of evidence accumulation and cluster detection, CVGIP 46, 327-345 (1989).
17. G. L. Scott, The alternative snake and other animals, Stockholm Workshop Comput. Vision, J. -O. Eklundh, ed., Stockholm, Sweden (1987).
18. M. Kass, A. Witkin and D. Terzopoulos, Snakes: Active contour models, Proc. 1st Int. Conf. Comput. Vision, 259-268, London (1987).
19. F. Leymarie and M. D. Levine, Tracking deformable objects in the plane using an active contour model, IEEE Trans. PAMI-15(6), 617-634 (1993).