A Comparative Study of Different Auto-Focus Methods for Mycobacterium Tuberculosis Detection from Brightfield Microscopic Images
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Date
2016
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PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING, VLSI, ELECTRICAL CIRCUITS AND ROBOTICS (DISCOVER)
Abstract
Automatic 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 brightfield microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on brightfield microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features.
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Keywords
Computer Science; Engineering; Robotics
Citation
,;95-100