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
Link To Document :
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