Dinkelbach NCUT: An Efficient Framework for Solving Normalized Cuts Problems with Priors and Convex Constraints

In this paper, we propose a novel framework, called Dinkelbach NCUT (DNCUT), which efficiently solves the normalized graph cut (NCUT) problem under general, convex constraints, as well as, under given priors on the nodes of the graph. Current NCUT methods use generalized eigen-decomposition, which p...

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Vydané v:	International journal of computer vision Ročník 89; číslo 1; s. 40 - 55
Hlavní autori:	Ghanem, Bernard, Ahuja, Narendra
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.08.2010 Springer Springer Nature B.V
Predmet:	Algorithms Applied sciences Artificial Intelligence Combinatorics Combinatorics. Ordered structures Complexity Computer Imaging Computer Science Computer science; control theory; systems Cost function Exact sciences and technology Filled plastics Graph theory Graphs Image Processing and Computer Vision Information retrieval. Graph Mathematical models Mathematics Pattern Recognition Pattern Recognition and Graphics Pattern recognition. Digital image processing. Computational geometry Programming Sciences and techniques of general use Segmentation Studies Theoretical computing Vision Conjugate gradient method Eigen-decomposition Dinkelbach method for fractional programming Multi-way segmentation Graph theory Interactive segmentation Graph-based image segmentation Quadratic programming Graph cuts Normalized graph cuts Initialization Image processing Iterative method Convex programming Global solution Image segmentation Graph cut Equality constraint Binary image Sparse matrix Problem solving Convexity Fractional programming
ISSN:	0920-5691, 1573-1405
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