Variational methods in image segmentation
Variational methods in image segmentation
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Global Minimum for Active Contour Models: A Minimal Path Approach
International Journal of Computer Vision
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
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
Yet Another Survey on Image Segmentation: Region and Boundary Information Integration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Tracking Objects Using Density Matching and Shape Priors
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Computing Geodesics and Minimal Surfaces via Graph Cuts
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Globally Optimal Geodesic Active Contours
Journal of Mathematical Imaging and Vision
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Comparing clusterings: an axiomatic view
ICML '05 Proceedings of the 22nd international conference on Machine learning
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
International Journal of Computer Vision
Toward Objective Evaluation of Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised segmentation of natural images via lossy data compression
Computer Vision and Image Understanding
A customized Gabor filter for unsupervised color image segmentation
Image and Vision Computing
Image segmentation based on GrabCut framework integrating multiscale nonlinear structure tensor
IEEE Transactions on Image Processing
Colour, texture, and motion in level set based segmentation and tracking
Image and Vision Computing
Image segmentation by MAP-ML estimations
IEEE Transactions on Image Processing
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Exact optimization for Markov random fields with convex priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Toward a generic evaluation of image segmentation
IEEE Transactions on Image Processing
Localizing Region-Based Active Contours
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Segmentation using superpixels: A bipartite graph partitioning approach
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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This paper proposes an unsupervised variational segmentation approach of color-texture images. To improve the description ability, the compact multi-scale structure tensor, total variation flow, and color information are integrated to extract color-texture information. Since heterogeneous image object and nonlinear variation exist in color-texture image, it is not appropriate to use one single/multiple constant in the Chan and Vese (CV) model to describe each phase [1,2]. Therefore, a multiphase successive active contour model (MSACM) based on the multivariable Gaussian distribution is presented to describe each phase. As geodesic active contour (GAC) has a stronger ability in capturing boundary. To inherit the advantages of edge-based model and region-based model, we incorporate the GAC into the MSACM to enhance the detection ability for concave edge. Although multiphase optimization of our proposed MSACM is a NP hard problem, we can discretely and approximately solve it by a multilayer graph method. In addition, to segment the color-texture image automatically, an adaptive iteration convergence criterion is designed by incorporating the local Kullback-Leibler distance and global phase label, so that we can control the segmentation process converges. Comparing to state-of-the-art unsupervised segmentation methods on a substantial of color texture images, our approach achieves a significantly better performance on capture ability of homogeneous region/smooth boundary and accuracy.