Results 1 - 10 of 489

Active Contours without Edges

by Tony F. Chan, Luminita A. Vese , 2001
"... In this paper, we propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford--Shah functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by gradient. We minimize an energy ..."
Abstract - Cited by 1206 (38 self) - Add to MetaCart
In this paper, we propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford--Shah functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by gradient. We minimize

Statistical shape influence in geodesic active contours

by Michael E. Leventon, W. Eric, L. Grimson, Olivier Faugeras - In Proc. 2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Hilton Head, SC , 2000
"... A novel method of incorporating shape information into the image segmentation process is presented. We introduce a representation for deformable shapes and define a probability distribution over the variances of a set of training shapes. The segmentation process embeds an initial curve as the zero l ..."
Abstract - Cited by 396 (4 self) - Add to MetaCart
A novel method of incorporating shape information into the image segmentation process is presented. We introduce a representation for deformable shapes and define a probability distribution over the variances of a set of training shapes. The segmentation process embeds an initial curve as the zero

Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation

by Nikos Paragios, Rachid Deriche - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2002
"... This paper presents a novel variational framework to deal with frame partition problems in Computer Vision. This framework exploits boundary and region-based segmentation modules under a curve-based optimization objective function. The task of supervised texture segmentation is considered to demonst ..."
Abstract - Cited by 312 (9 self) - Add to MetaCart
by unifying region and boundary-based information as an improved Geodesic Active Contour Model. The defined objective function is minimized using a gradient-descent method where a level set approach is used to implement the obtained PDE. According to this PDE, the curve propagation towards the final solution

Fast Global Minimization of the Active Contour/Snake Model

by Xavier Bresson, Pierre Vandergheynst, Stanley Osher, et al.
"... The active contour/snake model is one of the most successful variational models in image segmentation. It consists of evolving a contour in images toward the boundaries of objects. Its success is based on strong mathematical properties and efficient numerical schemes based on the level set method. ..."
Abstract - Cited by 161 (10 self) - Add to MetaCart
The active contour/snake model is one of the most successful variational models in image segmentation. It consists of evolving a contour in images toward the boundaries of objects. Its success is based on strong mathematical properties and efficient numerical schemes based on the level set method

A geometric snake model for segmentation of medical imagery

by Anthony Yezzi, Satyanad Kichenassamy, Arun Kumar, Peter Olver, Allen Tannenbaum - IEEE Transactions on Medical Imaging , 1997
"... Abstract — In this note, we employ the new geometric active contour models formulated in [25] and [26] for edge detection and segmentation of magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound medical imagery. Our method is based on defining feature-based metrics on a given i ..."
Abstract - Cited by 152 (20 self) - Add to MetaCart
Abstract — In this note, we employ the new geometric active contour models formulated in [25] and [26] for edge detection and segmentation of magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound medical imagery. Our method is based on defining feature-based metrics on a given

A shape-based approach to the segmentation of medical imagery using level sets

by Andy Tsai, Anthony Yezzi, William Wells, Clare Tempany, Dewey Tucker, Ayres Fan, W. Eric Grimson, Alan Willsky - IEEE Trans. Med. Imag , 2003
"... Abstract—We propose a shape-based approach to curve evolution for the segmentation of medical images containing known object types. In particular, motivated by the work of Leventon, Grimson, and Faugeras [15], we derive a parametric model for an implicit representation of the segmenting curve by app ..."
Abstract - Cited by 172 (11 self) - Add to MetaCart
Abstract—We propose a shape-based approach to curve evolution for the segmentation of medical images containing known object types. In particular, motivated by the work of Leventon, Grimson, and Faugeras [15], we derive a parametric model for an implicit representation of the segmenting curve

Fast Moving Object Segmentation Based On Active Contours

by unknown authors
"... Abstract—Active contour method is widely used in the image processing field. Recently, it has been used in object segmentation and has attracted great attention. However, most of the existing object segmentation methods based on active contours are complex and time-consuming. They cannot be used in ..."
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in some real-time applications. Hence, in this paper, a fast and efficient moving object segmentation algorithm based on an improved active contour model is proposed. Firstly, moving regions are detected based on frame differences. Then their boundaries are extracted and used as the coarse objects

Shape-based active contours for fast video segmentation

by Sasan Mahmoodi - IEEE Signal Process. Lett , 2009
"... Abstract—In this letter, we propose a shape-based active contours method for segmentation, based on a piecewise-constant approximation of the Mumford–Shah (M–S) functional. The Chan–Vese (C–V) formalism in a level set framework is used to formulate our method; however no sign distance function (SDF) ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
Abstract—In this letter, we propose a shape-based active contours method for segmentation, based on a piecewise-constant approximation of the Mumford–Shah (M–S) functional. The Chan–Vese (C–V) formalism in a level set framework is used to formulate our method; however no sign distance function (SDF

Object categorization by learned universal visual dictionary

by J. Winn, A. Criminisi, T. Minka - IN ICCV , 2005
"... This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class models are automatically learned from a set of training images. The method is simple and extremely fast, making it suitable ..."
Abstract - Cited by 302 (8 self) - Add to MetaCart
This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class models are automatically learned from a set of training images. The method is simple and extremely fast, making

Active contour based segmentation of medical image series

by Luo Xiping, Tian Jie
"... Abstract: In this paper, we propose an algorithm for the semiautomatic segmentation of medical image series based on the combination of the live wire algorithm and the active contour model. We modify the traditional live wire algorithm by combining it with the region growing method and obtain accura ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract: In this paper, we propose an algorithm for the semiautomatic segmentation of medical image series based on the combination of the live wire algorithm and the active contour model. We modify the traditional live wire algorithm by combining it with the region growing method and obtain
Results 1 - 10 of 489