Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
On active contour models and balloons
CVGIP: Image Understanding
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
Image Segmentation by Data-Driven Markov Chain Monte Carlo
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
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Optimal Mass Transport for Registration and Warping
International Journal of Computer Vision
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures
Journal of Mathematical Imaging and Vision
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
Fuzzy region competition: a convex two-phase segmentation framework
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Histogram based segmentation using Wasserstein distances
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow
IEEE Transactions on Image Processing
MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
Tracking by means of geodesic region models applied to multidimensional and complex medical images
Computer Vision and Image Understanding
Texture segmentation via non-local non-parametric active contours
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
Entropy-Scale profiles for texture segmentation
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications
A robust patch-statistical active contour model for image segmentation
Pattern Recognition Letters
Reduced set density estimator for object segmentation based on shape probabilistic representation
Journal of Visual Communication and Image Representation
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Tensor-SIFT Based Earth Mover's Distance for Contour Tracking
Journal of Mathematical Imaging and Vision
Active contour model driven by local histogram fitting energy
Pattern Recognition Letters
A linear programming based method for joint object region matching and labeling
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Fast two-stage segmentation via non-local active contours in multiscale texture feature space
Pattern Recognition Letters
Texture segmentation using vector-valued Chan-Vese model driven by local histogram
Computers and Electrical Engineering
Exact Histogram Specification for Digital Images Using a Variational Approach
Journal of Mathematical Imaging and Vision
Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop
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We propose and analyze a nonparametric region-based active contour model for segmenting cluttered scenes. The proposed model is unsupervised and assumes pixel intensity is independently identically distributed. Our proposed energy functional consists of a geometric regularization term that penalizes the length of the partition boundaries and a region-based image term that uses histograms of pixel intensity to distinguish different regions. More specifically, the region data encourages segmentation so that local histograms within each region are approximately homogeneous. An advantage of using local histograms in the data term is that histogram differentiation is not required to solve the energy minimization problem. We use Wasserstein distance with exponent 1 to determine the dissimilarity between two histograms. The Wasserstein distance is a metric and is able to faithfully measure the distance between two histograms, compared to many pointwise distances. Moreover, it is insensitive to oscillations, and therefore our model is robust to noise. A fast global minimization method based on (Chan et al. in SIAM J. Appl. Math. 66(5):1632---1648, 2006; Bresson et al. in J. Math. Imaging Vis. 28(2):151---167, 2007) is employed to solve the proposed model. The advantages of using this method are two-fold. First, the computational time is less than that of the method by gradient descent of the associated Euler-Lagrange equation (Chan et al. in Proc. of SSVM, pp. 697---708, 2007). Second, it is able to find a global minimizer. Finally, we propose a variant of our model that is able to properly segment a cluttered scene with local illumination changes.