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A multi-layer 'gas of circles' Markov random field model for the extraction of overlapping near-circular objects.

Nemeth, J. and Kato, Z. and Jermyn, I.H. (2011) 'A multi-layer 'gas of circles' Markov random field model for the extraction of overlapping near-circular objects.', in Advanced Concepts for Intelligent Vision Systems: 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011, proceedings. Heidelberg: Springer, pp. 171-182. Lecture notes in computer science. (8192).


We propose a multi-layer binary Markov random field (MRF) model that assigns high probability to object configurations in the image domain consisting of an unknown number of possibly touching or overlapping near-circular objects of approximately a given size. Each layer has an associated binary field that specifies a region corresponding to objects. Overlapping objects are represented by regions in different layers. Within each layer, long-range interactions favor connected components of approximately circular shape, while regions in different layers that overlap are penalized. Used as a prior coupled with a suitable data likelihood, the model can be used for object extraction from images, e.g. cells in biological images or densely-packed tree crowns in remote sensing images. We present a theoretical and experimental analysis of the model, and demonstrate its performance on various synthetic and biomedical images.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Publisher statement:The final publication is available at Springer via
Date accepted:No date available
Date deposited:13 April 2016
Date of first online publication:August 2011
Date first made open access:No date available

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