期刊
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
卷 34, 期 3, 页码 564-573出版社
IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2011.144
关键词
Sampling step size; shape from focus; 3D shape recovery; optical microscopy; curve fitting
资金
- National Research Foundation of Korea (NRF)
- Ministry of Education, Science, and Technology [2010-0008312]
- National Research Foundation of Korea [2010-0008312] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Shape from focus (SFF), which relies on image focus as a cue within sequenced images, represents a passive technique in recovering object shapes in scenes. Although numerous methods have been recently proposed, less attention has been paid to particular factors affecting them. In regard to SFF, one such critical factor impacting system application is the total number of images. A large data set requires a huge amount of computation power, whereas decreasing the number of images causes shape reconstruction to be crude and erroneous. The total number of images is inversely proportional to interframe distance or sampling step size. In this paper, interframe distance (or sampling step size) criteria for SFF systems have been formulated. In particular, light ray focusing is approximated by the use of a Gaussian beam followed by the formulation of a sampling expression using Nyquist sampling. Consequently, a fitting function for focus curves is also obtained. Experiments are performed on simulated and real objects to validate the proposed schemes.
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