Reflectance parameter estimation and its application to surface inspection

Real-Time Imaging

Volumn 4, Issue 6, 1998, Pages 429-442

  Yun, Il Dong ^a,c   Lee, Sang Uk ^b,c  

^a Hankuk University of Foreign Studies   (South Korea)

^b Seoul National University   (South Korea)

^c South Korea   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CHARGE COUPLED DEVICES; GENETIC ALGORITHMS; IMAGE ANALYSIS; IMAGE QUALITY; LIGHT REFLECTION; MATHEMATICAL MODELS; PARAMETER ESTIMATION;

LASER FINDERS; REFLECTANCE PARAMETER ESTIMATION; TORRANCE-SPARRO REFLECTANCE MODELS;

COMPUTER VISION;

EID: 0032269576     PISSN: 10072014     EISSN: None     Source Type: Journal    
DOI: 10.1006/rtim.1997.0105     Document Type: Article

References (19)

1. Torrance, K.E. & Sparrow, E.M. (1967) Theory for offspecular reflection from roughened surfaces. Journal of Optical Society of America, 57: 1105-1114.
2. Phong, BT. (1975) Illumination for computer generated pictures. Communications of the ACM, 18: 311-317.
3. Nayar, S.K., Ikeuchi, K. & Kanade, T. (1991) Surface reflection: physical and geometrical perpectives. IEEE Trans. Pattern Analysis and Machine Intelligence, 13: 611-634.
4. Wolff, L.B. (1992) Diffuse reflection (intensity reflectance model). Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 472-478, Champaign.
5. Wolff, L.B. (1994) Relative brightness of specular and diffuse reflection. Optical Engineering, 33: 285-293.
6. Ikeuchi, K. & Sato, K. (1991) Determining reflectance properties of an object using range and brightness images. IEEE Trans. Pattern Analysis and Machine Intelligence, 13: 1139-1153.
7. Kay, G. & Caelli, T. (1994) Inverting an illumination mode from range and intensity maps. CVGIP: Image Understanding, 59: 183-201.
8. Baribeau, R., Rioux, M. & Godin, G. (1992) Color reflectance modeling using a polychromatic laser range sensor. IEEE Trans. Pattern Analysisand Machine Intelligence, 14.
9. Nayar, SK., Ikeuchi, K. & Kanade, T. (1990) Determining shape and reflectance of hybrid surfaces by photometric sampling. IEEE Trans. Robotics and Automation, 6: 418-431.
10. Horn, B.K.P. (1986) Robot Vision. MIT Press.
11. Tagare, H.D. & de Figuaredo, R.J.P. (1991) A theory of photometric stereo for a class of diffuse non-lambertian surfaces. IEEE Trans. Pattern Analysis and Machine Intelligence, 13: 133-152.
12. Press, W.H., Flannery, B.P., Teukolsky, SA. & Vetterling, W.T. (1988) Numerical Recipes in C: The Art of Scientific Computing. Cambridge: Cambridge University Press.
13. Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Publishing Company.
14. DeJong, K.A. (1975) Analysis of the behavior of a class of genetic adaptive system. Ph.D. Thesis, Dept. of Computer and Communication Science, Univ. of Michigan.
15. Yao, L. (1994) Nonlinear parameter estimation via the genetic algorithm. IEEE Trans. Sgnal Processing, 42(4): 927-935.
16. Nicodemus, F.E., Richmond, J.C., Hsia, J.J. & Ginsberg, I.W. (1977) Geometrical Considerations and Nomenclature for Reflectance. Bolder CO: National Bureau of Standards.
17. SERVO ROBOT Inc. (1993) SCAN-3000 USER'S GUIDE.
18. Oren, M. & Nayar, S.K. (1995) Generalization of thelambertian mode and implications for machine vision. International Journal of Computer Vision, 14: 227-251.
19. Rousseeuw, P.J. (1984) Least median of squares regression. Journal of American Statistical Association, 79(388): 871-879.