Three-dimensional generalized Hough transform for object identification

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 1192, Issue , 1990, Pages 363-374

  Lou, Wang He ^a   Reeves, Anthony P ^a  

^a School of Operations Research and Industrial Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861607260     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.969749     Document Type: Conference Paper

References (10)

1. P. V. C. Hough, “Method and Means for Recognizing Complex Patterns,” U. S. Patent 3069654(Dec. 18, 1962).
2. R. O. Duda and P. E. Hart, “Use of the Hough Transform to Detect Lines and Curves in Pictures,” CACM 15(1) pp. 11-15 (1975).
3. C. Kimme, D. H. Ballard, and J. Sklansky, “Finding Circles by an Array of Accumulators,” Commun. Assoc. Comput. Mach. 18 pp. 120-122 (1975).
4. H. Wechsler and J. Sklansky, “Automatic Detection of Ribs in Chest Radiographs,” Pattern Recognition 9 pp. 21-30 (1977).
5. P. M. Merlin and D. J. Farber, “A Parallel Mechanism for Detecting Curves in Pictures,” IEEE Trans. Computer C-24 pp. 96-98 (Jan. 1975).
6. D. H. Ballard, “Generalizing the Hough Transform to Detect Arbitrary Shapes,” Parttern Recognition 13(2) pp. 111-122(1981).
7. D. J. Hunt, L. W. Nolte, and W. H. Ruedger, “Performance of the Hough Transform and Its Relationship to Statistical Signal Detection Theory,” Computer Vision, Graphics & Image Processing 43 pp. 221-238 (1988).
8. A. P. Reeves and Wang-he Lou, “Object Identification Using the Tuned Generalized Hough Transform,” Proc. 1987 IEEE International Conf. on Systems, Man & Cybernetics 1 pp. 124-128 IEEE Publishing Services, Alexandria VA(Oct. 20 1987).
9. Wang-He Lou and Anthony P. Reeves, “The Shape Information Distribution on a Three-Dimensional Object,” The 12th GRETSI Symposium on Signal and Image Processing, Nice, France(June, 1989).
10. A. P. Reeves, R. J. Prokop, and R. W. Taylor, “Shape Analysis of Three Dimension Objects Using range Information,” Conference on Computer Vision and Recognition, pp. 452-457 (1985).