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Graph Cuts and Efficient N-D Image Segmentation

by Yuri Boykov, Gareth Funka-Lea , 2006
"... Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of graph-cuts: segmentation of objects in image data. Despite its simplicity, this application epitomizes the best features ..."
Abstract - Cited by 307 (7 self) - Add to MetaCart
of combinatorial graph cuts methods in vision: global optima, practical efficiency, numerical robustness, ability to fuse a wide range of visual cues and constraints, unrestricted topological properties of segments, and applicability to N-D problems. Graph cuts based approaches to object extraction have also been

Efficient graph-based image segmentation.

by Pedro F Felzenszwalb , Daniel P Huttenlocher - International Journal of Computer Vision, , 2004
"... Abstract. This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show ..."
Abstract - Cited by 940 (1 self) - Add to MetaCart
Abstract. This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show

Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images

by Yuri Y. Boykov , Marie-Pierre Jolly , 2001
"... In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph ..."
Abstract - Cited by 1010 (20 self) - Add to MetaCart
In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph

The Contourlet Transform: An Efficient Directional Multiresolution Image Representation

by Minh N. Do, Martin Vetterli - IEEE TRANSACTIONS ON IMAGE PROCESSING
"... The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure t ..."
Abstract - Cited by 513 (20 self) - Add to MetaCart
flexible multiresolution, local, and directional image expansion using contour segments, and thus it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise

"GrabCut” -- interactive foreground extraction using iterated graph cuts

by Carsten Rother, Vladimir Kolmogorov, Andrew Blake - ACM TRANS. GRAPH , 2004
"... The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently ..."
Abstract - Cited by 1130 (36 self) - Add to MetaCart
The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors

SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries

by James Z. Wang, Jia Li, Gio Wiederhold - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2001
"... The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and Web image classification and searching. We present here SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries), an imag ..."
Abstract - Cited by 551 (35 self) - Add to MetaCart
The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and Web image classification and searching. We present here SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries

Geodesic Active Contours

by Vicent Caselles, Ron Kimmel, Guillermo Sapiro , 1997
"... A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both in ..."
Abstract - Cited by 1425 (47 self) - Add to MetaCart
. Formal results concerning existence, uniqueness, stability, and correctness of the evolution are presented as well. The scheme was implemented using an efficient algorithm for curve evolution. Experimental results of applying the scheme to real images including objects with holes and medical data imagery

TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-Class Object . . .

by J. Shotton, J. Winn, C. Rother, A. Criminisi - IN ECCV , 2006
"... This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned model is used for automatic visual recognition and semantic segmentation of photographs. Our discriminative model exploits nov ..."
Abstract - Cited by 426 (17 self) - Add to MetaCart
novel features, based on textons, which jointly model shape and texture. Unary classification and feature selection is achieved using shared boosting to give an efficient classifier which can be applied to a large number of classes. Accurate image segmentation is achieved by incorporating

NeTra: A toolbox for navigating large image databases

by Wei-ying Ma, B.S. Manjunath - Multimedia Systems , 1999
"... . We present here an implementation of NeTra, a prototype image retrieval system that uses color, texture, shape and spatial location information in segmented image regions to search and retrieve similar regions from the database. A distinguishing aspect of this system is its incorporation of a robu ..."
Abstract - Cited by 382 (15 self) - Add to MetaCart
attributes that represent each of these regions are computed. In addition to image segmentation, other important components of the system include an efficient color representation, and indexing of color, texture, and shape features for fast search and retrieval. This representation allows the user to compose

An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation

by Zhenyu Wu, Richard Leahy - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
Abstract - Cited by 360 (0 self) - Add to MetaCart
A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices
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