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Proceedings Paper

Camera calibration and performance evaluation of depth from defocus (DFD)
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Paper Abstract

Real-time and accurate autofocusing of stationary and moving objects is an important problem in modern digital cameras. Depth From Defocus (DFD) is a technique for autofocusing that needs only two or three images recorded with different camera parameters. In practice, there exist many factors that affect the performance of DFD algorithms, such as nonlinear sensor response, lens vignetting, and magnification variation. In this paper, we present calibration methods and algorithms for these three factors. Their correctness and effects on the performance of DFD have been investigated with experiments.

Paper Details

Date Published: 7 November 2005
PDF: 10 pages
Proc. SPIE 6000, Two- and Three-Dimensional Methods for Inspection and Metrology III, 60000A (7 November 2005); doi: 10.1117/12.631194
Show Author Affiliations
Tao Xian, State Univ. of New York at Stony Brook (United States)
Murali Subbarao, State Univ. of New York at Stony Brook (United States)


Published in SPIE Proceedings Vol. 6000:
Two- and Three-Dimensional Methods for Inspection and Metrology III
Kevin G. Harding, Editor(s)

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