%0 Conference Paper %B International Conference on Pattern Recognition (ICPR) %D 2012 %T A Multi-Layer Phase Field Model for Extracting Multiple Near-Circular Objects %A Csaba Molnar %A Zoltan Kato %A Ian Jermyn %E Jan-Olof Eklundh %E Yuichi Ohta %E Steven Tanimoto %X

This paper proposes a functional that assigns low `energy' to sets of subsets of the image domain consisting of a number of possibly overlapping near-circular regions of approximately a given radius: a `gas of circles'. The model can be used as a prior for object extraction whenever the objects conform to the `gas of circles' geometry, e.g. cells in biological images. Configurations are represented by a multi-layer phase field. Each layer has an associated function, regions being defined by thresholding. Intra-layer interactions assign low energy to configurations consisting of non-overlapping near-circular regions, while overlapping regions are represented in separate layers. Inter-layer interactions penalize overlaps. Here we present a theoretical and experimental analysis of the model.

 

%B International Conference on Pattern Recognition (ICPR) %I IEEE %C Tsukuba, Japan %P 1427 - 1430 %8 Nov 2012 %@ 978-1-4673-2216-4 %G eng %9 Conference paper %M 13324819 %0 Book Section %B Advances Concepts for Intelligent Vision Systems (ACIVS) %D 2011 %T A Multi-Layer 'Gas of Circles' Markov Random Field Model for the Extraction of Overlapping Near-Circular Objects %X

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.

%B Advances Concepts for Intelligent Vision Systems (ACIVS) %S Lecture Notes in Computer Science %I Springer-Verlag %C Ghent, Belgium %P 171 - 182 %8 Aug 2011 %@ 978-3-642-23686-0 %G eng %U http://www.inf.u-szeged.hu/ipcg/publications/Year/2011.complete.xml#Nemeth-etal2011 %9 Conference paper %! LNCS %R 10.1007/978-3-642-23687-7_16 %0 Journal Article %J PATTERN RECOGNITION %D 2009 %T A higher-order active contour model of a 'gas of circles' and its application to tree crown extraction %A Peter Horvath %A Ian Jermyn %A Zoltan Kato %A Josiane Zerubia %B PATTERN RECOGNITION %V 42 %P 699 - 709 %8 2009/// %@ 0031-3203 %G eng %N 5 %! PATTERN RECOGN %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %D 2009 %T Kör alakú objektumok szegmentálása Markov mező segítségével %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %I Akaprint %C Budapest %P 1 - 9 %8 Jan 2009 %G hun %U http://vision.sztaki.hu/~kepaf/kepaf2009_CD/files/116-4-MRFCircle08.pdf %9 Conference paper %0 Book Section %B 16th IEEE International Conference on Image Processing (ICIP) %D 2009 %T A Markov random field model for extracting near-circular shapes %A Tamás Blaskovics %A Zoltan Kato %A Ian Jermyn %X

We propose a binary Markov Random Field (MRF) model that assigns high probability to regions in the image domain consisting of an unknown number of circles of a given radius. We construct the model by discretizing the 'gas of circles' phase field model in a principled way, thereby creating an 'equivalent'MRF. The behaviour of the resultingMRF model is analyzed, and the performance of the new model is demonstrated on various synthetic images as well as on the problem of tree crown detection in aerial images. ©2009 IEEE.

%B 16th IEEE International Conference on Image Processing (ICIP) %I IEEE %C Cairo, Egypt %P 1073 - 1076 %8 Nov 2009 %@ 978-1-4244-5653-6 %G eng %9 Conference paper %R 10.1109/ICIP.2009.5413472 %0 Conference Paper %B Proceedings of the European Signal Processing Conference (EUSIPCO) %D 2007 %T A 'gas of Circles' Phase Field Model and its Application to Tree Crown Extraction %A Peter Horvath %A Ian Jermyn %E Marek Domanski %E Ryszard Stasinski %E Maciej Bartkowiak %B Proceedings of the European Signal Processing Conference (EUSIPCO) %C Poznan, Poland %8 2007 %9 Conference paper %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 %D 2007 %T Kör alakú objektumok szegmentálása magasabb rendű aktív kontúr modellek segítségével %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 %I Képfeldolgozók és Alakfelismerők Társasága %C Debrecen %P 133 - 140 %8 Jan 2007 %G eng %9 Conference paper %0 Conference Paper %B Proceedings of the International Conference on Computer Analysis of Images and Patterns (CAIP) %D 2007 %T A New Phase Field Model of a 'gas of Circles' for Tree Crown Extraction from Aerial Images %A Peter Horvath %A Ian Jermyn %E Walter G. Kropatsch %E Martin Kampel %E Allan Hanbury %B Proceedings of the International Conference on Computer Analysis of Images and Patterns (CAIP) %C Vienna, Austria %V 4673 %P 702-709 %8 2007 %9 Conference paper %R 10.1007/978-3-540-74272-2_87 %0 Book Section %B Proceedings of the18th International Conference on Pattern Recognition, ICPR 2006 %D 2006 %T A higher-order active contour model for tree detection %X

We present a model of a 'gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. The method uses the recently introduced 'higher order active contours' (HOACs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. This makes them ideal when looking for multiple instances of an entity in an image. We study an existing HOAC model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. Combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. The model has many other potential applications. © 2006 IEEE.

%B Proceedings of the18th International Conference on Pattern Recognition, ICPR 2006 %I IEEE %P 130 - 133 %8 2006/// %G eng %0 Conference Paper %B Proceedings of the International Conference on Pattern Recognition (ICPR) %D 2006 %T A Higher-Order Active Contour Model for Tree Detection %A Peter Horvath %A Ian Jermyn %A Zoltan Kato %A Josiane Zerubia %X

We present a model of a 'gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. The method uses the recently introduced 'higher order active contours' (HOACs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. This makes them ideal when looking for multiple instances of an entity in an image. We study an existing HOAC model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. Combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. The model has many other potential applications.

%B Proceedings of the International Conference on Pattern Recognition (ICPR) %I IAPR %C Hong Kong, China %V 2 %P 130–133 %8 2006 %9 Conference paper %0 Generic %D 2006 %T A Higher-Order Active Contour Model of a `Gas of Circles' and its Application to Tree Crown Extraction %8 2006/// %G eng %0 Book Section %B Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) %D 2006 %T An Improved `Gas of Circles' Higher-Order Active Contour Model and its Application to Tree Crown Extraction %B Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) %I Springer Verlag %C Berlin; Heidelberg; New York %P 152 - 161 %8 2006/// %G eng %0 Book Section %B Joint Hungarian-Austrian conference on image processing and pattern recognition. 5th conference of the Hungarian Association for Image Processing and Pattern Recognition (KÉPAF), 29th workshop of the Austrian Association for Pattern Reco %D 2005 %T Shape Moments for Region Based Active Contours %B Joint Hungarian-Austrian conference on image processing and pattern recognition. 5th conference of the Hungarian Association for Image Processing and Pattern Recognition (KÉPAF), 29th workshop of the Austrian Association for Pattern Reco %I OCG %C Vienna %P 187 - 194 %8 2005/// %G eng