International Journal of Computer Vision
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Learning a Classification Model for Segmentation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active contours driven by local Gaussian distribution fitting energy
Signal Processing
The Split Bregman Method for L1-Regularized Problems
SIAM Journal on Imaging Sciences
A soft multiphase segmentation model via Gaussian mixture
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A unified tensor level set for image segmentation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction
Journal of Scientific Computing
A Multiphase Image Segmentation Method Based on Fuzzy Region Competition
SIAM Journal on Imaging Sciences
Example-based image color and tone style enhancement
ACM SIGGRAPH 2011 papers
Image segmentation by iterated region merging with localized graph cuts
Pattern Recognition
Image smoothing via L0 gradient minimization
Proceedings of the 2011 SIGGRAPH Asia Conference
Pattern Recognition
Dirichlet Gaussian mixture model: Application to image segmentation
Image and Vision Computing
A local region-based Chan-Vese model for image segmentation
Pattern Recognition
Natural image segmentation with adaptive texture and boundary encoding
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Multiband Image Segmentation and Object Recognition for Understanding Road Scenes
IEEE Transactions on Intelligent Transportation Systems
Multi-task low-rank affinity pursuit for image segmentation
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Latent Low-Rank Representation for subspace segmentation and feature extraction
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Segmentation of color images using a linguistic 2-tuples model
Information Sciences: an International Journal
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This paper introduces a novel variational segmentation method within the fuzzy framework, which solves the problem of segmenting multi-region color-scale images of natural scenes. We call this kind of images as natural images. The advantages of our segmentation method are: (1) by introducing the PCA descriptors, our segmentation model can partition color-texture images better than classical variational-based segmentation models, (2) to preserve geometrical structure of each fuzzy membership function, we propose a nonconvex regularization term in our model, (3) to solve our segmentation model more efficiently, we design a fast iteration algorithm in which we integrate the augmented Lagrange multiplier method and the iterative reweighting. We conduct comprehensive experiments to measure the segmentation performance of our model in terms of visual evaluation, and we also demonstrate the efficiency of the corresponding algorithm in terms of a variety of quantitative indices. The proposed model achieves better segmentation results compared with some other well-known models, such as the level-set model and the fuzzy region competition model, while the proposed algorithm is much more efficient than the algorithm of the state-of-the-art natural image segmentation model.