Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours

DOI10.4208/eajam.090312.080412azbMath1284.68623OpenAlexW2328195514MaRDI QIDQ5406916

Ke Chen, Noor Badshah, Ghulam Murtaza, Haider Ali

Publication date: 4 April 2014

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/6f7a711a777c9fed1797883e29b2931ed3fc1e6a

zbMATH Keywords

total variationlevel setsegmentationcoefficient of variationfunctional minimisiation

Mathematics Subject Classification ID

Order statistics; empirical distribution functions (62G30) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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Cites Work

• Multiphase image segmentation using a phase-field model
• Geodesic active contour under geometrical conditions: theory and 3D applications
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• Segmentation under geometrical conditions using geodesic active contours and interpolation using level set methods
• A multiphase level set framework for image segmentation using the Mumford and Shah model
• Level set methods and dynamic implicit surfaces
• Optimal approximations by piecewise smooth functions and associated variational problems
• Active contours without edges
• Matrix Preconditioning Techniques and Applications

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