A modular approach on adaptive thresholding for extraction of mammalian cell regions from bioelectric images in complex lighting environments

Inder K. Purohit; Praveen Sankaran; K. Vijayan Asari; Mohammad A. Karim

doi:10.1117/12.777852

3 April 2008 A modular approach on adaptive thresholding for extraction of mammalian cell regions from bioelectric images in complex lighting environments

Inder K. Purohit, Praveen Sankaran, K. Vijayan Asari, Mohammad A. Karim

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Proceedings Volume 6978, Visual Information Processing XVII; 697807 (2008) https://doi.org/10.1117/12.777852
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

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Inder K. Purohit, Praveen Sankaran, K. Vijayan Asari, and Mohammad A. Karim "A modular approach on adaptive thresholding for extraction of mammalian cell regions from bioelectric images in complex lighting environments", Proc. SPIE 6978, Visual Information Processing XVII, 697807 (3 April 2008); https://doi.org/10.1117/12.777852

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Light sources and illumination

Image filtering

Binary data

Image contrast enhancement

Image processing

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