Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection by Helmholtz Principle
Journal of Mathematical Imaging and Vision
Fast and Robust Segmentation of Natural Color Scenes
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume I - Volume I
A Grouping Principle and Four Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
An a contrario Decision Framework for Region-Based Motion Detection
International Journal of Computer Vision
An A Contrario Decision Method for Shape Element Recognition
International Journal of Computer Vision
Bottom-Up Hierarchical Image Segmentation Using Region Competition and the Mumford-Shah Functional
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
A new graph cut-based multiple active contour algorithm without initial contours and seed points
Machine Vision and Applications
Performance Modeling and Algorithm Characterization for Robust Image Segmentation
International Journal of Computer Vision
Stopping region-based image segmentation at meaningful partitions
SAMT'07 Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia
Adaptive vision leveraging digital retinas: extracting meaningful segments
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Patch-Based texture edges and segmentation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
IEEE Transactions on Image Processing
A contrario hierarchical image segmentation
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatically finding clusters in normalized cuts
Pattern Recognition
SIAM Journal on Imaging Sciences
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Segmenting an image into homogeneous regions generally involves a decision criterion to establish whether two adjacent regions are similar. Decisions should be adaptive to get robust and accurate segmentation algorithms, avoid hazardous a priori and have a clear interpretation. We propose a decision process based on a contrario reasoning: two regions are meaningfully different if the probability of observing such a difference in pure noise is very low. Since the existing analytical methods are intractable in our case, we extend them to allow a mixed use of analytical computations and Monte-Carlo simulations. The resulting decision criterion is tested experimentally through a simple merging algorithm, which can be used as a post-filtering and validation step for existing segmentation methods.