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Robust image binarization with ensembles of thresholding algorithms

[+] Author Affiliations
Farid Melgani

University of Trento, Department of Information and Communication Technologies, Via Sommarive, 14, I-38050 Trento, Italy

J. Electron. Imaging. 15(2), 023010 (May 02, 2006). doi:10.1117/1.2194767
History: Received June 19, 2005; Revised November 15, 2005; Accepted November 30, 2005; Published May 02, 2006
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The effectiveness of a thresholding algorithm strongly depends on the image statistical characteristics. In a completely unsupervised context, this makes it difficult to choose the most appropriate algorithm to binarize a given image. This issue is considered through a novel thresholding strategy based on the fusion of an ensemble of different thresholding algorithms and formulated within a Markov random field (MRF) framework. The obtained experimental results suggest that in general the fusion of an ensemble of thresholding algorithms leads to a robust thresholding system, and in particular the proposed MRF strategy represents an effective solution to carry out the fusion process.

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Topics

Algorithms

Citation

Farid Melgani
"Robust image binarization with ensembles of thresholding algorithms", J. Electron. Imaging. 15(2), 023010 (May 02, 2006). ; http://dx.doi.org/10.1117/1.2194767


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