Abstract
Segmentation is an important research area in image analysis. In particular, effective segmentation methods play an essential role in the computerization of the analysis, classification, and quantification of biological images for high content screening. Image segmentation based on thresholding has many practical and useful applications because it is simple and computationally efficient. Different methods based on different criteria of optimality give different choices of thresholds. This paper introduces a method for optimal thresholding in gray-scale images by mimizing the variograms of object and background pixels. The mathematical formulation of the proposed technique is very easy for computer implementation. The experimental results have shown the superior performance of the new method over some popular models for the segmentation cell images.
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Pham, T.D. (2007). Geo-Thresholding for Segmentation of Fluorescent Microscopic Cell Images. In: Perner, P., Salvetti, O. (eds) Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry. MDA 2007. Lecture Notes in Computer Science(), vol 4826. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76300-0_2
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DOI: https://doi.org/10.1007/978-3-540-76300-0_2
Publisher Name: Springer, Berlin, Heidelberg
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