The Experts below are selected from a list of 3789 Experts worldwide ranked by ideXlab platform
Kalman Palagyi - One of the best experts on this subject based on the ideXlab platform.
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a sequential 3d curve Thinning Algorithm based on isthmuses
International Symposium on Visual Computing, 2014Co-Authors: Kalman PalagyiAbstract:Curve-Thinning is a frequently applied technique to obtain centerlines from volumetric binary objects. Conventional curve-Thinning Algorithms preserve endpoints to provide important geometric information relative to the objects. An alternative strategy is also proposed that accumulates isthmuses (i.e., generalization of curve interior points as elements of the centerlines). This paper presents a computationally efficient sequential isthmus-based 3D curve-Thinning Algorithm.
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an order independent sequential Thinning Algorithm
International Workshop on Combinatorial Image Analysis, 2009Co-Authors: Peter Kardos, Gabor Nemeth, Kalman PalagyiAbstract:Thinning 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.
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IWCIA - An Order---Independent Sequential Thinning Algorithm
Lecture Notes in Computer Science, 2009Co-Authors: Peter Kardos, Gabor Nemeth, Kalman PalagyiAbstract:Thinning 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.
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a 3d fully parallel surface Thinning Algorithm
Theoretical Computer Science, 2008Co-Authors: Kalman PalagyiAbstract:The Thinning is an iterative layer by layer erosion until only the ''skeletons'' of the objects are left. This paper presents a Thinning Algorithm for extracting medial surfaces from 3D binary pictures. The strategy which is used is called fully parallel, which means that the same parallel operator is applied at each iteration. An efficient implementation of the proposed Algorithm on conventional sequential computers is given and the topological correctness for (26, 6) binary pictures is proved.
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A 3-subiteration 3D Thinning Algorithm for extracting medial surfaces
Pattern Recognition Letters, 2002Co-Authors: Kalman PalagyiAbstract:Abstract Thinning is an iterative layer by layer erosion for extracting skeletons. This paper presents an efficient 3D parallel Thinning Algorithm which produces medial surfaces. A 3-subiteration strategy is proposed: the Thinning operation is changed from iteration to iteration with a period of 3 according to the three deletion directions.
Gilles Bertrand - One of the best experts on this subject based on the ideXlab platform.
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a parallel Thinning Algorithm for grayscale images
Discrete Geometry for Computer Imagery, 2013Co-Authors: Michel Couprie, Nivando Bezerra, Gilles BertrandAbstract:Grayscale skeletonization offers an interesting alternative to traditional skeletonization following a binarization. It is well known that parallel Algorithms for skeletonization outperform sequential ones in terms of quality of results, yet no general and well defined framework has been proposed until now for parallel grayscale Thinning. We introduce in this paper a parallel Thinning Algorithm for grayscale images, and prove its topological soundness based on properties of the critical kernels framework. The Algorithm and its proof, given here in the 2D case, are also valid in 3D. Some applications are sketched in conclusion.
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a 3d 6 subiteration curve Thinning Algorithm based on p simple points
International Workshop on Combinatorial Image Analysis, 2005Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study C. Lohou, G. Bertrand [A new 3D 12-subiteration Thinning Algorithm based on P-simple points, in: International Workshop on Combinatorial Image Analysis, IWCIA 2001, Philadelphia, PA, USA, ENTCS, vol. 46, 2001, pp. 39-58; A new 3D 6-subiteration Thinning Algorithm based on P-simple points, in: International Conference on Discrete Geometry for Computer Imagery, DGCI'2002, Bordeaux, France, ENTCS, vol. 2301, Springer, Berlin, 2002, pp. 102-113; A 3D 12-subiteration Thinning Algorithm based on P-simple points, Discrete Appl. Math. 139(1-3) (2004) 171-195.], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A^' from an existent Thinning Algorithm A, such that A^' deletes at least all the points removed by A, while preserving the same end points (in particular, we have already proposed a 12-subiteration Thinning Algorithm C. Lohou, G. Bertrand [International Workshop on Combinatorial Image Analysis, IWCIA 2001, Philadelphia, PA, USA, ENTCS, vol. 46, 2001, pp. 39-58; A 3D 12-subiteration Thinning Algorithm based on P-simple points, Discrete Appl. Math. 139(1-3) (2004) 171-195.]). In this paper, by applying this methodology, we propose a 6-subiteration curve Thinning Algorithm which deletes at least all the points removed by two 6-subiteration curve Thinning Algorithms: either the one proposed by Palagyi and Kuba [A 3D 6-subiteration Thinning Algorithm for extracting medial lines, Pattern Recogn. Lett. 19(7) (1998) 613-627.], or the one proposed by Gong and Bertrand [A simple parallel 3D Thinning Algorithm, in: International Conference on Pattern Recognition, Atlantic City, NJ, USA, 1990, pp. 188-190.]. .
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a 3d 12 subiteration Thinning Algorithm based on p simple points
International Workshop on Combinatorial Image Analysis, 2004Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In this paper, we propose a new methodology to conceive a Thinning scheme based on the parallel deletion of P-simple points. This scheme needs neither a preliminary labelling nor an extended neighborhood, in the opposite of the already proposed Thinning Algorithms based on P-simple points. Moreover, from an existent Thinning Algorithm A, we construct another Thinning Algorithm A', such that A' deletes at least all the points removed by A, while preserving the same end points. In fact, we propose a 12-subiteration Thinning Algorithm which deletes at least the points removed by the one proposed by Palagyi and Kuba (Graphical Models Image Process. 61 (1999) 199).
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a new 3d 6 subiteration Thinning Algorithm based on p simple points
Discrete Geometry for Computer Imagery, 2002Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study [1], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A' from an existent Thinning Algorithm A, such that A' deletes at least all the points removed by A, while preserving the same end points.In this paper, by applying this methodology, we propose a new 6-subiteration Thinning Algorithm which deletes at least all the points removed by the 6-subiteration Thinning Algorithm proposed by Palagyi and Kuba [2].
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DGCI - A New 3D 6-Subiteration Thinning Algorithm Based on P-Simple Points
Discrete Geometry for Computer Imagery, 2002Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study [1], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A' from an existent Thinning Algorithm A, such that A' deletes at least all the points removed by A, while preserving the same end points.In this paper, by applying this methodology, we propose a new 6-subiteration Thinning Algorithm which deletes at least all the points removed by the 6-subiteration Thinning Algorithm proposed by Palagyi and Kuba [2].
Christophe Lohou - One of the best experts on this subject based on the ideXlab platform.
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Automatic Correction of Ma and Sonka's Thinning Algorithm Using P-Simple Points
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010Co-Authors: Christophe Lohou, Julien DehosAbstract:Ma and Sonka proposed a fully parallel 3D Thinning Algorithm which does not always preserve topology. We propose an Algorithm based on P-simple points which automatically corrects Ma and Sonka's Algorithm. As far as we know, our Algorithm is the only fully parallel curve Thinning Algorithm which preserves topology.
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a 3d 6 subiteration curve Thinning Algorithm based on p simple points
International Workshop on Combinatorial Image Analysis, 2005Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study C. Lohou, G. Bertrand [A new 3D 12-subiteration Thinning Algorithm based on P-simple points, in: International Workshop on Combinatorial Image Analysis, IWCIA 2001, Philadelphia, PA, USA, ENTCS, vol. 46, 2001, pp. 39-58; A new 3D 6-subiteration Thinning Algorithm based on P-simple points, in: International Conference on Discrete Geometry for Computer Imagery, DGCI'2002, Bordeaux, France, ENTCS, vol. 2301, Springer, Berlin, 2002, pp. 102-113; A 3D 12-subiteration Thinning Algorithm based on P-simple points, Discrete Appl. Math. 139(1-3) (2004) 171-195.], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A^' from an existent Thinning Algorithm A, such that A^' deletes at least all the points removed by A, while preserving the same end points (in particular, we have already proposed a 12-subiteration Thinning Algorithm C. Lohou, G. Bertrand [International Workshop on Combinatorial Image Analysis, IWCIA 2001, Philadelphia, PA, USA, ENTCS, vol. 46, 2001, pp. 39-58; A 3D 12-subiteration Thinning Algorithm based on P-simple points, Discrete Appl. Math. 139(1-3) (2004) 171-195.]). In this paper, by applying this methodology, we propose a 6-subiteration curve Thinning Algorithm which deletes at least all the points removed by two 6-subiteration curve Thinning Algorithms: either the one proposed by Palagyi and Kuba [A 3D 6-subiteration Thinning Algorithm for extracting medial lines, Pattern Recogn. Lett. 19(7) (1998) 613-627.], or the one proposed by Gong and Bertrand [A simple parallel 3D Thinning Algorithm, in: International Conference on Pattern Recognition, Atlantic City, NJ, USA, 1990, pp. 188-190.]. .
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a 3d 12 subiteration Thinning Algorithm based on p simple points
International Workshop on Combinatorial Image Analysis, 2004Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In this paper, we propose a new methodology to conceive a Thinning scheme based on the parallel deletion of P-simple points. This scheme needs neither a preliminary labelling nor an extended neighborhood, in the opposite of the already proposed Thinning Algorithms based on P-simple points. Moreover, from an existent Thinning Algorithm A, we construct another Thinning Algorithm A', such that A' deletes at least all the points removed by A, while preserving the same end points. In fact, we propose a 12-subiteration Thinning Algorithm which deletes at least the points removed by the one proposed by Palagyi and Kuba (Graphical Models Image Process. 61 (1999) 199).
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a new 3d 6 subiteration Thinning Algorithm based on p simple points
Discrete Geometry for Computer Imagery, 2002Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study [1], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A' from an existent Thinning Algorithm A, such that A' deletes at least all the points removed by A, while preserving the same end points.In this paper, by applying this methodology, we propose a new 6-subiteration Thinning Algorithm which deletes at least all the points removed by the 6-subiteration Thinning Algorithm proposed by Palagyi and Kuba [2].
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DGCI - A New 3D 6-Subiteration Thinning Algorithm Based on P-Simple Points
Discrete Geometry for Computer Imagery, 2002Co-Authors: Christophe Lohou, Gilles BertrandAbstract:In a recent study [1], we proposed a new methodology to build Thinning Algorithms based on the deletion of P-simple points. This methodology may permit to conceive a Thinning Algorithm A' from an existent Thinning Algorithm A, such that A' deletes at least all the points removed by A, while preserving the same end points.In this paper, by applying this methodology, we propose a new 6-subiteration Thinning Algorithm which deletes at least all the points removed by the 6-subiteration Thinning Algorithm proposed by Palagyi and Kuba [2].
P.i. Rockett - One of the best experts on this subject based on the ideXlab platform.
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An improved rotation-invariant Thinning Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005Co-Authors: P.i. RockettAbstract:Ahmed and Ward [Sept. 1995] have recently presented an elegant, rule-based rotation-invariant Thinning Algorithm to produce a single-pixel wide skeleton from a binary image. We show examples where this Algorithm fails on two-pixel wide lines and propose a modified method which corrects this shortcoming based on graph connectivity.
F.b. Sheikh - One of the best experts on this subject based on the ideXlab platform.
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Rotation invariant Thinning Algorithm to detect ridge bifurcations for fingerprint identification
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005Co-Authors: P.m. Patil, S.r. Suralkar, F.b. SheikhAbstract:In this paper we have modified the Thinning Algorithm proposed by Ahmed and Ward (2002). The unique feature that distinguishes the Algorithm is its ability to thin any symbol or fingerprint to its central line taking care that the shape of the symbol is preserved while being rotation invariant. Our modified Algorithm also incorporates a process to thin zigzag diagonal lines having a width of two pixels which was not considered in "a rotation invariant rule-based Thinning Algorithm for character recognition" (Ahmed and Ward, 2002). The Algorithm is iterative and makes use of parallel processing to speed up execution. The system has 21 rules in its inference engine which are applied simultaneously to every pixel in each iteration. The Algorithm is implemented for Thinning fingerprints, fonts and symbols to a single pixel width. We also introduce a 24 rule based mask for detection of ridge bifurcations, which can be helpful for recognition/authentication of fingerprints as a biometric
