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Proceedings Paper

A modular approach on adaptive thresholding for extraction of mammalian cell regions from bioelectric images in complex lighting environments
Author(s): Inder K. Purohit; Praveen Sankaran; K. Vijayan Asari; Mohammad A. Karim
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Paper Abstract

A modular approach on an adaptive thresholding method for segmentation of cell regions in bioelectric images with complex lighting environments and background conditions is presented in this paper. Preprocessing steps involve lowpass filtering of the image and local contrast enhancement. This image is then adaptively thresholded which produces a binary image. The binary image consists of cell regions and the edges of a metal electrode that show up as bright spots. A local region based approach is used to distinguish between cell regions and the metal electrode tip that cause bright spots. Regional properties such as area are used to separate the cell regions from the non-cell regions. Special emphasis is given on the detection of twins and triplet cells with the help of watershed transformation, which might have been lost if form-factor alone were to be used as the geometrical descriptor to separate the cell and the non-cell regions.

Paper Details

Date Published: 3 April 2008
PDF: 11 pages
Proc. SPIE 6978, Visual Information Processing XVII, 697807 (3 April 2008); doi: 10.1117/12.777852
Show Author Affiliations
Inder K. Purohit, Old Dominion Univ. (United States)
Praveen Sankaran, Old Dominion Univ. (United States)
K. Vijayan Asari, Old Dominion Univ. (United States)
Mohammad A. Karim, Old Dominion Univ. (United States)


Published in SPIE Proceedings Vol. 6978:
Visual Information Processing XVII
Zia-ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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