Proceedings Article10.1109/ACSSC.2001.987670
Image segmentation using curve evolution
Baris Sumengen,B.S. Manjunath,Charles Kenney +2 more
- 01 Jan 2001
- Vol. 2, pp 1141-1145
TL;DR: The proposed approach thus utilizes an edge-based segmentation method and extends traditional PDE based curve evolution methods to texture image segmentation, and avoids the post processing problems in edge linking and boundary detection.
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Abstract: A novel scheme for image segmentation is presented. The technique is based on the integration of ideas from geodesic active contours and a previously proposed edgeflow segmentation. Given an image a 2-D vector is constructed at each pixel location. This vector points in the direction of potential boundary pixels. The computation of the 2-D vector field is based on image intensity, color and texture gradients. Following this, an initial curve is instantiated and propagated to separate the image into foreground and background regions. The curve propagation is guided by the above mentioned vector field. The proposed approach thus utilizes an edge-based segmentation method and extends traditional PDE based curve evolution methods to texture image segmentation, and avoids the post processing problems in edge linking and boundary detection.
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Citations
Method for segmentation of IVUS image sequences
TL;DR: In this paper, a method for performing segmentation of an interior vessel within the body of a patient is presented. And the method includes extracting a preliminary outer boundary of the interior vessel, tracking images in each of the batches to counter various distortions, performing statistical analysis and spatial integration on each batch to obtain a classification of blood and tissue regions.
187
Level set segmentation of remotely sensed hyperspectral images
James E Ball,Lori M. Bruce +1 more
- 25 Jul 2005
TL;DR: A semi-automated supervised hyperspectral image segmentation algorithm based on the level set methodology is presented, which shows the efficacy of the new algorithm using well-known supervised parallepiped or maximum-likelihood classification methods provided in the ERDAS Imagine software suite.
Accuracy analysis of hyperspectral imagery classification using level sets
John E. Ball,Lori M. Bruce +1 more
- 01 Jan 2006
TL;DR: In this article, the authors presented a semi-automated supervised level set-based hyperspectral image segmentation algorithm (LSHSA) using specialized speed functions created using pixel similarity and class discriminator functions.
Texture segmentation through salient texture patches
Lech Szumilas,Allan Hanbury +1 more
- 01 Jan 2006
TL;DR: This work gives a proof of concept that the stable salient texture regions supported by a semi-automatic segmentation algorithm may provide fully automatic image segmentation into uniform color and/or texture regions.
Survey on the Image Segmentation
张新峰,沈兰荪 +1 more
TL;DR: This survey introduces edge-based and domain-based image segmentation methods, discussing their advantages and limitations, as well as physics-based approaches and evaluation metrics, with a forecast of future developments in the field of image segmentation.
References
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Normalized cuts and image segmentation
Jianbo Shi,Jitendra Malik +1 more
TL;DR: This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups.
Normalized cuts and image segmentation
Jianbo Shi,Jitendra Malik +1 more
- 17 Jun 1997
TL;DR: This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups.
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Stanley Osher,James A. Sethian +1 more
TL;DR: The PSC algorithm as mentioned in this paper approximates the Hamilton-Jacobi equations with parabolic right-hand-sides by using techniques from the hyperbolic conservation laws, which can be used also for more general surface motion problems.
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Active contours without edges
Tony F. Chan,Luminita A. Vese +1 more
TL;DR: A new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level sets is proposed, which can detect objects whose boundaries are not necessarily defined by the gradient.