Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.fss.2006.10.006 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
image segmentation,fuzzy color homogeneity,fuzzy image segmentation,fuzzy color,fuzzy connectivity,suitable t-norm,path-based image segmentation proposal,homogeneity degree,color homogeneity measure,aggregate resemblance,weber t-norm,color image segmentation,fuzzy segmentation,segmentation process,region-based fit,functional relationship,path-based segmentation,homogeneity measure | Homogeneity (statistics),Scale-space segmentation,Segmentation,Fuzzy logic,Image segmentation,Fuzzy set,Artificial intelligence,Pixel,Machine learning,Mathematics,Minimum spanning tree-based segmentation | Journal |
Volume | Issue | ISSN |
158 | 3 | Fuzzy Sets and Systems |
Citations | PageRank | References |
13 | 0.65 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Belen Prados-Suárez | 1 | 17 | 1.49 |
| J. Chamorro-Martínez | 2 | 93 | 5.99 |
| Daniel Sánchez | 3 | 124 | 15.47 |
| Javier Abad | 4 | 14 | 0.99 |