Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
Watershed of a continuous function
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatically determine the membership function based on the maximum entropy principle
Information Sciences: an International Journal
Watershed-based segmentation and region merging
Computer Vision and Image Understanding
Edge Detection with Embedded Confidence
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
Computer Vision
Digital Image Processing
SOM Ensemble-Based Image Segmentation
Neural Processing Letters
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
Multispectral image segmentation by a multichannel watershed-based approach
International Journal of Remote Sensing
Watersheds, mosaics, and the emergence paradigm
Discrete Applied Mathematics - Special issue: Advances in discrete geometry and topology (DGCI 2003)
Fuzzy Sets and Systems
Comparison between immersion-based and toboggan-based watershed image segmentation
IEEE Transactions on Image Processing
Proceedings of the 6th International Symposium on Visual Information Communication and Interaction
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Neutrosophy studies the origin, nature, scope of neutralities, and their interactions with different ideational spectra. It is a new philosophy to extend the fuzzy logic and is the basis of neutrosophic logic, neutrosophic probability, neutrosophic set, and neutrosophic statistics. Image segmentation is a key step for image processing, pattern recognition, computer vision. Many existing methods for image description, classification, and recognition highly depend on the segmentation results. In this paper, neutrosophy is applied to image processing by defining a neutrosophic domain, which is described by three subsets T, I, and F. Then we employ watershed algorithm to perform segmentation of the image in the neutrosophic domain. The experiments show that the proposed method can get better results comparing with that obtained by the existing methods.