Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/7268
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dc.contributor.authorSaini, G.
dc.contributor.authorPanicker, R.O.
dc.contributor.authorSoman, B.
dc.contributor.authorRajan, J.
dc.date.accessioned2020-03-30T09:58:44Z-
dc.date.available2020-03-30T09:58:44Z-
dc.date.issued2016
dc.identifier.citation2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings, 2016, Vol., , pp.95-100en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7268-
dc.description.abstractAutomatic tuberculosis (TB) detection methods using microscopic images are becoming more popular now a days. Auto-focusing is the first and foremost step in the development of an automated microscope for TB detection. Different focus measures exist for the selection of in-focus image from both fluorescence and bright field microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on bright field microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features. � 2016 IEEE.en_US
dc.titleA comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic imagesen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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