00454nas a2200133 4500008004100000245004100041210004100082260003800123300001400161100002000175700002300195700002100218856008100239 2013 eng d00aParallel Thinning Based on Isthmuses0 aParallel Thinning Based on Isthmuses aVeszprémbNJSZT-KÉPAFcJan 2013 a512 - 5251 aNémeth, Gábor1 aPalágyi, Kálmán1 aCzúni, László uhttps://www.inf.u-szeged.hu/publication/parallel-thinning-based-on-isthmuses01250nas a2200157 4500008004100000020001400041245008300055210006900138260006500207300001300272490000700285520064000292100001900932700002000951856012100971 2013 eng d a0324-721X00aSpectrum Skeletonization: A New Method for Acoustic Signal Feature Extraction.0 aSpectrum Skeletonization A New Method for Acoustic Signal Featur aSzegedbUniversity of Szeged, Institute of Informaticsc2013 a89 - 1030 v213 a
Vibration Analysis Tests (VAT) and Acoustic Emission tests (AE) are used in several industrial applications. Many of them perform analysis in the frequency domain. Peaks in the power density spectrum hold relevant information about acoustic events. In this paper we propose a novel method for feature extraction of vibration samples by analyzing the shape of their auto power spectrum density function. The approach uses skeletonization techniques in order to find the hierarchical structure of the spectral peaks. The proposed method can be applied as a preprocessing step for spectrum analysis of vibration signals.
1 aDobján, Tibor1 aNémeth, Gábor uhttps://www.inf.u-szeged.hu/publication/spectrum-skeletonization-a-new-method-for-acoustic-signal-feature-extraction01191nas a2200181 4500008004100000020002200041245005600063210005600119260002600175300001400201520058900215100002300804700002000827700001900847700002400866700002300890856009600913 2012 eng d a978-94-007-4173-700aTopology Preserving Parallel 3D Thinning Algorithms0 aTopology Preserving Parallel 3D Thinning Algorithms bSpringer-Verlagc2012 a165 - 1883 aA widely used technique to obtain skeletons of binary objects is thinning, which is an iterative layer-by-layer erosion in a topology preserving way. Thinning in 3D is capable of extracting various skeleton-like shape descriptors (i.e., centerlines, medial surfaces, and topological kernels). This chapter describes a family of new parallel 3D thinning algorithms for (26, 6) binary pictures. The reported algorithms are derived from some sufficient conditions for topology preserving parallel reduction operations, hence their topological correctness is guaranteed.
1 aPalágyi, Kálmán1 aNémeth, Gábor1 aKardos, Péter1 aBrimkov, Valentin E1 aBarneva, Reneta, P uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-3d-thinning-algorithms01310nas a2200181 4500008004100000020002300041245006600064210006500130260004000195300001400235520067200249100002000921700002300941700002100964700002200985700001501007856010601022 2011 eng d a978-1-4577-0841-1 00a2D Parallel Thinning Algorithms Based on Isthmus-Preservation0 a2D Parallel Thinning Algorithms Based on IsthmusPreservation aDubrovnik, CroatiabIEEEcSep 2011 a585 - 5903 aSkeletons are widely used shape descriptors which summarize the general form of binary objects. A technique to obtain skeletons is the thinning, that is an iterative layer-by-layer erosion in a topology-preserving way. Conventional thinning algorithms preserve line endpoints to provide important geometric information relative to the object to be represented. Bertrand and Couprie proposed an alternative strategy by accumulating isthmus points that are line interior points. In this paper we present six new 2D parallel thinning algorithms that are derived from some sufficient conditions for topology preserving reductions and based on isthmus-preservation.
1 aNémeth, Gábor1 aPalágyi, Kálmán1 aLončarić, Sven1 aRamponi, Giovanni1 aSersic, D. uhttps://www.inf.u-szeged.hu/publication/2d-parallel-thinning-algorithms-based-on-isthmus-preservation01305nas a2200169 4500008004100000020001400041245009600055210006900151260006500220300001400285490000700299520063100306100002000937700001900957700002300976856013600999 2011 eng d a0324-721X00a2D parallel thinning and shrinking based on sufficient conditions for topology preservation0 a2D parallel thinning and shrinking based on sufficient condition aSzegedbUniversity of Szeged, Institute of Informaticsc2011 a125 - 1440 v203 aThinning and shrinking algorithms, respectively, are capable of extracting medial lines and topological kernels from digital binary objects in a topology preserving way. These topological algorithms are composed of reduction operations: object points that satisfy some topological and geometrical constraints are removed until stability is reached. In this work we present some new sufficient conditions for topology preserving parallel reductions and fiftyfour new 2D parallel thinning and shrinking algorithms that are based on our conditions. The proposed thinning algorithms use five characterizations of endpoints.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/2d-parallel-thinning-and-shrinking-based-on-sufficient-conditions-for-topology-preservation01818nas a2200217 4500008004100000020002200041245008300063210006900146260004500215300001200260520102200272100002001294700001901314700002301333700002201356700002301378700002401401700002801425700002401453856012301477 2011 eng d a978-3-642-21072-300aA family of topology-preserving 3d parallel 6-subiteration thinning algorithms0 afamily of topologypreserving 3d parallel 6subiteration thinning aMadrid, SpainbSpringer VerlagcMay 2011 a17 - 303 aThinning is an iterative layer-by-layer erosion until only the skeleton-like shape features of the objects are left. This paper presents a family of new 3D parallel thinning algorithms that are based on our new sufficient conditions for 3D parallel reduction operators to preserve topology. The strategy which is used is called subiteration-based: each iteration step is composed of six parallel reduction operators according to the six main directions in 3D. The major contributions of this paper are: 1) Some new sufficient conditions for topology preserving parallel reductions are introduced. 2) A new 6-subiteration thinning scheme is proposed. Its topological correctness is guaranteed, since its deletion rules are derived from our sufficient conditions for topology preservation. 3) The proposed thinning scheme with different characterizations of endpoints yields various new algorithms for extracting centerlines and medial surfaces from 3D binary pictures. © 2011 Springer-Verlag Berlin Heidelberg.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aAggarwal, Jake, K1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aKoroutchev, Kostadin, N1 aKorutcheva, Elka, R uhttps://www.inf.u-szeged.hu/publication/a-family-of-topology-preserving-3d-parallel-6-subiteration-thinning-algorithms00520nas a2200157 4500008004100000245006000041210006000101260002800161300001400189100001900203700002000222700002300242700001700265700002300282856005700305 2011 eng d00aIterációnkénti simítással kombinált vékonyítás0 aIterációnkénti simítással kombinált vékonyítás aSzegedbNJSZTcJan 2011 a174 - 1891 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_01.pdf01086nas a2200169 4500008004100000020001400041245008100055210006900136260001300205300001400218490000700232520049400239100002000733700001900753700002300772856012100795 2011 eng d a1524-070300aThinning combined with iteration-by-iteration smoothing for 3D binary images0 aThinning combined with iterationbyiteration smoothing for 3D bin cNov 2011 a335 - 3450 v733 aIn this work we present a new thinning scheme for reducing the noise sensitivity of 3D thinning algorithms. It uses iteration-by-iteration smoothing that removes some border points that are considered as extremities. The proposed smoothing algorithm is composed of two parallel topology preserving reduction operators. An efficient implementation of our algorithm is sketched and its topological correctness for (26, 6) pictures is proved. © 2011 Elsevier Inc. All rights reserved.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/thinning-combined-with-iteration-by-iteration-smoothing-for-3d-binary-images00578nas a2200157 4500008004100000245010100041210007700142260002800219300001400247100002000261700001900281700002300300700001700323700002300340856005700363 2011 hun d00aA topológia-megőrzés elegendő feltételein alapuló 3D párhuzamos vékonyító algoritmusok0 atopológiamegőrzés elegendő feltételein alapuló 3D párhuzamos vék aSzegedbNJSZTcJan 2011 a190 - 2051 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_02.pdf01129nas a2200157 4500008004100000020001400041245005300055210005300108260003800161300001200199490000700211520061700218100002000835700002300855856009300878 2011 eng d a0899-945700aTopology Preserving Parallel Thinning Algorithms0 aTopology Preserving Parallel Thinning Algorithms bWiley Periodicals, Inc.cFeb 2011 a37 - 440 v213 aThinning is an iterative object reduction technique for extracting medial curves from binary objects. During a thinning process, some border points that satisfy certain topological and geometric constraints are deleted in iteration steps. Parallel thinning algorithms are composed of parallel reduction operators that delete a set of object points simultaneously. This article presents 21 parallel thinning algorithms for (8,4) binary pictures that are derived from the sufficient conditions for topology preservation accommodated to the three parallel thinning approaches. © 2011 Wiley Periodicals, Inc.
1 aNémeth, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-thinning-algorithms00495nas a2200157 4500008004100000020001400041245005300055210005300108260000900161300001200170490000700182100001900189700002000208700002300228856008600251 2010 eng d a0133-339900aBejárásfüggetlen szekvenciális vékonyítás0 aBejárásfüggetlen szekvenciális vékonyítás c2010 a17 - 400 v271 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/bejarasfuggetlen-szekvencialis-vekonyitas01180nas a2200181 4500008004100000245005800041210005700099260005200156300001400208520057500222100002000797700001900817700002300836700001300859700001500872700001300887856009800900 2010 eng d00aTopology preserving 2-subfield 3D thinning algorithms0 aTopology preserving 2subfield 3D thinning algorithms aInnsbruck, AustriabIASTED ACTA PresscFeb 2010 a310 - 3163 aThis paper presents a new family of 3D thinning algorithms for extracting skeleton-like shape features (i.e, centerline, medial surface, and topological kernel) from volumetric images. A 2-subfield strategy is applied: all points in a 3D picture are partitioned into two subsets which are alternatively activated. At each iteration, a parallel operator is applied for deleting some border points in the active subfield. The proposed algorithms are derived from Ma's sufficient conditions for topology preservation, and they use various endpoint characterizations.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aZagar, B1 aKuijper, A1 aSahbi, H uhttps://www.inf.u-szeged.hu/publication/topology-preserving-2-subfield-3d-thinning-algorithms01486nas a2200181 4500008004100000245007800041210006900119260005900188300001400247490000900261520081200270100002001082700001901102700002301121700002301144700001901167856011801186 2010 eng d00aTopology Preserving 3D Thinning Algorithms using Four and Eight Subfields0 aTopology Preserving 3D Thinning Algorithms using Four and Eight aPóvoa de Varzim, PortugalbSpringer VerlagcJune 2010 a316 - 3250 v61113 aThinning is a frequently applied technique for extracting skeleton-like shape features (i.e., centerline, medial surface, and topological kernel) from volumetric binary images. Subfield-based thinning algorithms partition the image into some subsets which are alternatively activated, and some points in the active subfield are deleted. This paper presents a set of new 3D parallel subfield-based thinning algorithms that use four and eight subfields. The three major contributions of this paper are: 1) The deletion rules of the presented algorithms are derived from some sufficient conditions for topology preservation. 2) A novel thinning scheme is proposed that uses iteration-level endpoint checking. 3) Various characterizations of endpoints yield different algorithms. © 2010 Springer-Verlag.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aCampilho, Aurélio1 aKamel, Mohamed uhttps://www.inf.u-szeged.hu/publication/topology-preserving-3d-thinning-algorithms-using-four-and-eight-subfields01333nas a2200217 4500008004100000245006400041210006400105260004400169300001400213490000900227520058400236100002000820700001900840700002300859700002300882700002400905700002500929700002600954700003100980856010401011 2010 eng d00aTopology Preserving Parallel Smoothing for 3D Binary Images0 aTopology Preserving Parallel Smoothing for 3D Binary Images aBuffalo, USAbSpringer VerlagcMay 2010 a287 - 2980 v60263 aThis paper presents a new algorithm for smoothing 3D binary images in a topology preserving way. Our algorithm is a reduction operator: some border points that are considered as extremities are removed. The proposed method is composed of two parallel reduction operators. We are to apply our smoothing algorithm as an iteration-by-iteration pruning for reducing the noise sensitivity of 3D parallel surface-thinning algorithms. An efficient implementation of our algorithm is sketched and its topological correctness for (26,6) pictures is proved. © 2010 Springer-Verlag.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aHauptman, Herbert, A1 aJorge, Renato M Natal1 aTavares, João, Manuel R S uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-smoothing-for-3d-binary-images03870nas a2200733 4500008004100000020001400041245008100055210006900136260027000205300001600475490000700491520149600498100002001994700002402014700002202038700002002060700001902080700002102099700001802120700002202138700002302160700001902183700002002202700001702222700001902239700002202258700002302280700001402303700002102317700002202338700002002360700002002380700002202400700002002422700002302442700002402465700002302489700002302512700001902535700001802554700001802572700001802590700001202608700001402620700002402634700002002658700002202678700002202700700002502722700002002747700002102767700002002788700002102808700002002829700002102849700002202870700002002892700001902912700002702931700002302958700002002981700001403001856012103015 2009 eng d a0278-006200aComparison and evaluation of methods for liver segmentation from CT datasets0 aComparison and evaluation of methods for liver segmentation from aPrice, K., Anything you can do, I can do better (no you can't) (1986) Comput. Vis. Graph. Image Process, 36 (2-3), pp. 387-391;S. G. Armato, G. McLennan, M. F. McNitt-Gray, C. R. Meyer, D. Yankelevitz, D. R. Aberle, C. I. Henschke, E. A. Hoffman, E. A. KacAug 2009 a1251 - 12650 v283 aThis paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques. © 2009 IEEE.
1 aHeimann, Tobias1 aVan Ginneken, Brahm1 aStyner, Martin, A1 aArzhaeva, Yulia1 aAurich, Volker1 aBauer, Christian1 aBeck, Andreas1 aBecker, Christoph1 aBeichel, Reinhardt1 aBekes, György1 aBello, Fernando1 aBinnig, Gerd1 aBischof, Horst1 aBornik, Alexander1 aCashman, Peter, MM1 aChi, Ying1 aCórdova, Andres1 aDawant, Benoit, M1 aFidrich, Márta1 aFurst, Jacob, D1 aFurukawa, Daisuke1 aGrenacher, Lars1 aHornegger, Joachim1 aKainmüller, Dagmar1 aKitney, Richard, I1 aKobatake, Hidefumi1 aLamecker, Hans1 aLange, Thomas1 aLee, Jeongjin1 aLennon, Brian1 aLi, Rui1 aLi, Senhu1 aMeinzer, Hans-Peter1 aNémeth, Gábor1 aRaicu, Daniela, S1 aRau, Anne-Mareike1 aVan Rikxoort, Eva, M1 aRousson, Mikael1 aRuskó, László1 aSaddi, Kinda, A1 aSchmidt, Günter1 aSeghers, Dieter1 aShimizu, Akinobi1 aSlagmolen, Pieter1 aSorantin, Erich1 aSoza, Grzegorz1 aSusomboon, Ruchaneewan1 aWaite, Jonathan, M1 aWimmer, Andreas1 aWolf, Ivo uhttps://www.inf.u-szeged.hu/publication/comparison-and-evaluation-of-methods-for-liver-segmentation-from-ct-datasets01191nas a2200181 4500008004100000020002200041245009900063210006900162260005600231300001400287520045800301100002300759700002000782700001800802700002700820700002300847856013900870 2009 eng d a978-3-642-04396-300aFully Parallel 3D Thinning Algorithms based on Sufficient Conditions for Topology Preservation0 aFully Parallel 3D Thinning Algorithms based on Sufficient Condit aMontreal, Quebec, CanadabSpringer VerlagcSep 2009 a481 - 4923 aThis paper presents a family of parallel thinning algorithms for extracting medial surfaces from 3D binary pictures. The proposed algorithms are based on sufficient conditions for 3D parallel reduction operators to preserve topology for (26,6) pictures. Hence it is self-evident that our algorithms are topology preserving. Their efficient implementation on conventional sequential computers is also presented. © 2009 Springer Berlin Heidelberg.
1 aPalágyi, Kálmán1 aNémeth, Gábor1 aBrlek, Srecko1 aReutenauer, Christophe1 aProvençal, Xavier uhttps://www.inf.u-szeged.hu/publication/fully-parallel-3d-thinning-algorithms-based-on-sufficient-conditions-for-topology-preservation00641nas a2200157 4500008004100000245009200041210007800133260003300211300001000244100001900254700002000273700002300293700002500316700002000341856012200361 2009 hun d00aKritikus párokat vizsgáló bejárásfüggetlen szekvenciális vékonyító algoritmus0 aKritikus párokat vizsgáló bejárásfüggetlen szekvenciális vékonyí aBudapestbAkaprintcJan 2009 a1 - 81 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aChetverikov, Dmitrij1 aSziranyi, Tamas uhttps://www.inf.u-szeged.hu/publication/kritikus-parokat-vizsgalo-bejarasfuggetlen-szekvencialis-vekonyito-algoritmus00635nas a2200169 4500008004100000245007400041210007200115260003300187300001100220100002000231700002100251700002300272700002000295700002500315700002000340856010500360 2009 eng d00aA morfológiai váz általánosítása szomszédsági szekvenciákkal0 amorfológiai váz általánosítása szomszédsági szekvenciákkal aBudapestbAkaprintcJan 2009 a1 - 101 aNémeth, Gábor1 aKovács, György1 aPalágyi, Kálmán1 aFazekas, Attila1 aChetverikov, Dmitrij1 aSziranyi, Tamas uhttps://www.inf.u-szeged.hu/publication/a-morfologiai-vaz-altalanositasa-szomszedsagi-szekvenciakkal01114nas a2200181 4500008004100000020002200041245005500063210005100118260005600169300001400225520052000239100001900759700002000778700002300798700002200821700002300843856006600866 2009 eng d a978-3-642-10208-000aAn order-independent sequential thinning algorithm0 aorderindependent sequential thinning algorithm aPlaya del Carmen, MexicobSpringer VerlagcNov 2009 a162 - 1753 aThinning is a widely used approach for skeletonization. Sequential thinning algorithms use contour tracking: they scan border points and remove the actual one if it is not designated a skeletal point. They may produce various skeletons for different visiting orders. In this paper, we present a new 2-dimensional sequential thinning algorithm, which produces the same result for arbitrary visiting orders and it is capable of extracting maximally thinned skeletons. © Springer-Verlag Berlin Heidelberg 2009.
1 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aWiederhold, Petra1 aBarneva, Reneta, P uhttp://link.springer.com/chapter/10.1007/978-3-642-10210-3_1301308nas a2200217 4500008004100000020002200041022001400063245006100077210006100138260004900199300001400248520057800262100002000840700002300860700002100883700002000904700002500924700001900949700002100968856010100989 2008 eng d a978-3-540-79546-9 a0302-974300aSkeletonization based on metrical neighborhood sequences0 aSkeletonization based on metrical neighborhood sequences aSantorini, GreecebSpringer VerlagcMay 2008 a333 - 3423 aSkeleton is a shape descriptor which summarizes the general formof objects. It can be expressed in terms of the fundamental morphological operations. The limitation of that characterization is that its construction based on digital disks such that cannot provide good approximation to the Euclidean disks. In this paper we define a new type of skeleton based on neighborhood sequences that is much closer to the Euclidean skeleton. A novel method for quantitative comparison of skeletonization algorithms is also proposed. © 2008 Springer- Verlag Berlin Heidelberg.
1 aFazekas, Attila1 aPalágyi, Kálmán1 aKovács, György1 aNémeth, Gábor1 aGasteratos, Antonios1 aVincze, Markus1 aTsotsos, John, K uhttps://www.inf.u-szeged.hu/publication/skeletonization-based-on-metrical-neighborhood-sequences