Name
Abstract | ||
|---|---|---|
This paper proposes to use case-based-reasoning for grey-level image segmentation. Different approaches to image segmentation have been proposed in the literature. The selection of the segmentation approach and the assignment of the values to the parameters involved in the selected algorithm depend on image domain and on the specific application. Case-based-reasoning seems a promising way to make the above selection automatic. In this paper, we describe the results of a preliminary study done in this respect. In particular, we refer to the automatic selection of the values of the parameters for a new watershed image segmentation algorithm. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1142/S0218001408006491 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
segmentation, watershed transformation, case-based-reasoning | Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Image texture,Segmentation-based object categorization,Image segmentation,Region growing,Artificial intelligence,Connected-component labeling,Minimum spanning tree-based segmentation,Machine learning | Journal |
Volume | Issue | ISSN |
22 | 5 | 0218-0014 |
Citations | PageRank | References |
10 | 0.57 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Frucci | 1 | 190 | 26.24 |
| Petra Perner | 2 | 1466 | 168.32 |
| sanniti di baja | 3 | 1169 | 149.96 |