Bayesian Ying-Yang machine, clustering and number of clusters
Pattern Recognition Letters - special issue on pattern recognition in practice V
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
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
Yet Another Survey on Image Segmentation: Region and Boundary Information Integration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
Neural Networks - New developments in self-organizing maps
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Guiding Model Search Using Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Comparing clusterings: an axiomatic view
ICML '05 Proceedings of the 22nd international conference on Machine learning
Fast nonparametric clustering with Gaussian blurring mean-shift
ICML '06 Proceedings of the 23rd international conference on Machine learning
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
TurboPixels: Fast Superpixels Using Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian framework for image segmentation with spatially varying mixtures
IEEE Transactions on Image Processing
A de-texturing and spatially constrained K-means approach for image segmentation
Pattern Recognition Letters
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Paper: Modeling by shortest data description
Automatica (Journal of IFAC)
Segmentation of Multivariate Mixed Data via Lossy Data Coding and Compression
IEEE Transactions on Pattern Analysis and Machine Intelligence
MDS-Based Multiresolution Nonlinear Dimensionality Reduction Model for Color Image Segmentation
IEEE Transactions on Neural Networks
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
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An unsupervised image segmentation method for natural images is proposed in this paper. We assume that texture features in natural images are distributed as a mixture of Gaussians. In order to cluster the extracted feature vectors, we modify a clustering algorithm based on Bayesian Ying-Yang (BYY) harmony learning theory with Dirichlet-Normal-Wishart prior. This algorithm can determine the number of components automatically during the clustering procedure, as long as we give a large enough initial component number. Our works in this paper have presented a complete pipeline of clustering-based image segmentation including feature extraction, robust feature clustering and methodological effective post processing. The experiments reported in this paper demonstrate that the proposed method is efficient (in terms of visual evaluation and quantitative performance measures) and performs competitively compared to the existing state-of-the-art segmentation methods.