Graphical Models and Image Processing
Multiseeded Segmentation Using Fuzzy Connectedness
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploiting color and topological features for region segmentation with recursive fuzzy C-means
Machine Graphics & Vision International Journal - Special issue on latest results in colour image processing and applications
Rough and Accurate Segmentation of Natural Color Images Using Fuzzy Region-Growing Algorithm
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
A Modified Fuzzy C-Means Algorithm for Segmentation of MRI
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
A New Color Image Segmentation Algorithm based on Watershed Transformation
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Algorithm of Clustering for Color Images Segmentation
CONIELECOMP '05 Proceedings of the 15th International Conference on Electronics, Communications and Computers
Color image segmentation using acceptable histogram segmentation
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Unsupervised color image segmentation using mean shift and deterministic annealing EM
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Segmentation of color images using multiscale clustering and graph theoretic region synthesis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy color histogram and its use in color image retrieval
IEEE Transactions on Image Processing
Color in image and video processing: most recent trends and future research directions
Journal on Image and Video Processing - Color in Image and Video Processing
Fuzzy filter based on interval-valued fuzzy sets for image filtering
Fuzzy Sets and Systems
Color image segmentation based on type-2 fuzzy sets and region merging
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
On dealing with imprecise information in a content based image retrieval system
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
Segmentation of color images using a linguistic 2-tuples model
Information Sciences: an International Journal
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In this paper we introduce an approach to automatically select a homogeneity measure for color image segmentation, on the basis of the characteristics of the region to be segmented. In a previous work we presented a fuzzy color path-based image segmentation proposal where membership degrees were computed from the connectivity between pixels, based on the homogeneity degree of the path joining them. To measure homogeneity, we aggregate resemblances between consecutive pixels using t-norms. Since a great variety of homogeneity measures can be found, we need to automatically select a suitable t-norm for a given region. For this purpose we firstly approximate a value characterizing the region surrounding the seed, studying a set of fixed paths. Secondly, we establish a functional relationship between this value and the parameter of a Weber t-norm. Based on this functional relationship we obtain the value of t-norm's parameter, corresponding to the homogeneity measure to be used in the segmentation process. We show that our approach performs well in different types of regions.