Abstract
Two new focus measure operators for Shape From Focus to estimate the three-dimensional shape of a surface are proposed in this paper. The images are formed by a camera using moving apertures. The well-focused image pixels are identified by frequency analysis or matching with the all-focused image of the scene. Frequency analysis involves the usage of classical focus measure operators and summing up for each aperture to find the focus quality to be maximized. The lesser method uses the match-points and error ratios of any matching algorithm used within an all-focused image region and all same-focus-different-aperture images to find the total displacement. The inverse of total displacement can be used as a focus quality measure. The experiments on real images show that the introduced ideas work effectively and efficiently.
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References
Aydin T, Akgül YS (2008) A new adaptive focus measure for shape from focus. British machine vision conference, Leeds (September)
Nair HN, Stewart CV (1992) Robust focus ranging. Computer Vision and Pattern Recognition, pp 309–314
Nayar SK, Nakagawa Y (August 1994) Shape from focus. Pattern Anal Mach Intell 16(8):824–831
Pratt WK (1978) Digital image processing. Wiley, New York
Scharstein D, Szeliski R (2003) High-accuracy stereo depth maps using structured light. Computer Vision and Pattern Recognition, p. 195–202, Wisconsin
Schechner YY, Kiryati N (2000) Depth from defocus versus stereo: how different really are they? Int J Comput Vis 39(2):141–162
Subbaro M, Surya G (1994) Depth from defocus: a spatial domain approach. Int J Comput Vis 13(3):271–294
Acknowledgments
This work was supported by TUBITAK Career Project 105E097.
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© 2013 Springer International Publishing Switzerland
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Sayar , M.S., Akgül, Y.S. (2013). Depth from Moving Apertures. In: Gelenbe, E., Lent, R. (eds) Information Sciences and Systems 2013. Lecture Notes in Electrical Engineering, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-01604-7_19
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DOI: https://doi.org/10.1007/978-3-319-01604-7_19
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