DocumentCode
2593178
Title
Autofocusing algorithm selection in computer microscopy
Author
Sun, Yu ; Duthaler, Stefan ; Nelson, Bradley J.
Author_Institution
Dept. of Mech. & Ind. Eng., Toronto Univ., Ont., Canada
fYear
2005
fDate
2-6 Aug. 2005
Firstpage
70
Lastpage
76
Abstract
Autofocusing is a fundamental technology for automated biological and biomedical analyses and is indispensable for routine use of microscopes on a large scale. This paper presents a comprehensive comparison study of 18 focus algorithms in which a total of 139,000 microscope images are analyzed. Six samples were used with three observation methods (bright field, phase contrast, an d differential interference contrast (DIC)) under two magnifications (100× and 400×). A ranking methodology is proposed, based on which the 18 focus algorithms are ranked. Image pre-processing is also conducted to extensively reveal the performance and robustness of the focus algorithms. The presented guidelines allow for the selection of the optimal focus algorithm for different microscopy applications.
Keywords
computerised instrumentation; focusing; medical image processing; microscopy; autofocusing algorithm selection; bright field; computer microscopy; differential interference contrast; phase contrast; ranking method; Algorithm design and analysis; Biology computing; Biomedical computing; Focusing; Guidelines; Image analysis; Interference; Large-scale systems; Microscopy; Robustness; autofocusing; microscopy; ranking; selection;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on
Print_ISBN
0-7803-8912-3
Type
conf
DOI
10.1109/IROS.2005.1545017
Filename
1545017
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