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Camera focusing based on fringe pattern matching

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Bryanston-Cross, P. and Wang, Zuobin. (1997) Camera focusing based on fringe pattern matching. Applied Optics, Vol.36 (No.25). pp. 6498-6502. ISSN 0003-6935

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Official URL: http://dx.doi.org/10.1364/AO.36.006498

Abstract

A method of camera focusing based on fringe pattern matching is presented. In the method, the variance of the mismatch function is used as a focus measure. The focus measure was examined in a fringe analysis system, and the results from the three well-known focus measures-gray-level variance, image gradient, and Laplacian-were also obtained in the experiment as a comparison. The: experimental results show that the focus measure based on fringe pattern matching performs well in peak sharpness, monotonicity, and noise sensitivity and that it has a better performance in noise sensitivity wing to its advantage of averaging noise.

Item Type:	Journal Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Autofocus cameras, Pattern recognition systems, Diffraction patterns
Journal or Publication Title:	Applied Optics
Publisher:	Optical Society of America
ISSN:	0003-6935
Date:	1 September 1997
Volume:	Vol.36
Number:	No.25
Number of Pages:	5
Page Range:	pp. 6498-6502
Identification Number:	10.1364/AO.36.006498
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
References:	1. M. Subbarao, T. Choi, and A. Nikzad, “Focusing techniques,” Opt. Eng. 32, 2824–2836 (1993). 2. J. H. Lee, K. S. Kim, B. D. Nam, J. C. Lee, Y. M. Kwon, and H. G. Kim, “Implementation of a passive automatic focusing algorithm for digital still camera,” IEEE Trans. Consumer Electron. 41, 449–454 (1995). 3. G. Lightart and F. Groen, “A comparison of different autofocus algorithms,” in Proceedings of IEEE International Conference on Pattern Recognition, (Institute of Electrical and Electronics Engineers, New York, 1982), pp. 597–600. 4. E. Krotkov, “Focusing,” Int. J. Comput. Vision 1, 223–237 (1987). 5. N. Akiyama, H. Makihira, and T. Nakata, “Automatic focusing method using stripe pattern projection technique II: subjects and countermeasures for practical use,” J. Jpn Soc. Precis. Eng. 56, 2273–2279 (1990). 6. A. Goshtasby, G. C. Stockman, and C. V. Page, “A region-based approach to digital image registration with subpixel accuracy,” IEEE Trans. Geosci. Remote Sensing GE-24, 390–399 (1986). 7. A. Kashko, H. Buxton, B. F. Buxton, and D. A. Castelow, “Parallel matching and reconstruction algorithms in computer vision,” Parallel Comput. 8, 3–17 (1988). 8. Z. Wang, P. J. Bryanston-Cross, and D. J. Whitehouse, “Phase difference determination by fringe pattern matching,” Opt. Laser Technol. 28, 417–422 (1996). 9. Z. Wang, M. S. Grac¸a, P. J. Bryanston-Cross, and D. J. Whitehouse, “Phase-shifted image matching algorithm for displacement measurement,” Opt. Eng. 35, 2327–2332 (1996). 10. K. R. Castleman, Digital Image Processing (Prentice-Hall, Englewood Cliffs, N.J., 1979). 11. M. K. Steven, Fundamentals of Statistical Signal Processing, Estimation Theory (Prentice-Hall International, London, 1993). 12. A. Novini, “Fundamentals of on-line gauging for machine vision,” in Close-Range Photogrammetry Meets Machine Vision, E. P. Baltsavias and A. Gruen, eds., Proc. SPIE 1395, 736–746 (1990). 13. J. F. W. Galyer and C. R. Shotbolt, Metrology for Engineers (Cassell, London, 1990). 14. A. Athanasios, Probability, Random Variables, and Stochastic Processes ~McGraw-Hill, New York, 1965).
URI:	http://wrap.warwick.ac.uk/id/eprint/16456