Name
Abstract | ||
|---|---|---|
In this paper we analyse the problem of image understanding at the knowledge level. We treat the problem as a design task and define a generic problem solving method (PSM) which allows us to tackle the task in a hierarchical and recursive way with subsumption. The main advantage of this generic PSM is the possibility to instantiate specific PSMs through parameter space configuration, which makes it possible to reuse this structure both in the task decomposition at different hierarchical levels and in different applications. This generic PSM was implemented following the well established foundations of Knowledge Engineering which prescribe the maintenance of the conceptual structure from the modeling stage at the knowledge level down to the particular implementation. Finally, we apply the proposed framework to the problem of optic nerve head identification in eye fundus images and particular results are presented. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-44868-3_74 | IWANN (1) |
Keywords | Field | DocType |
particular result,particular implementation,morphological clustering,different application,generic problem,knowledge level,different hierarchical level,conceptual structure,generic psm,task decomposition,design task,multi-dimensional image segmentation,image sensor,pattern recognition,curse of dimensionality,image segmentation,computer vision,feature space,image processing | Feature vector,Knowledge level,Reuse,Computer science,Image processing,Image segmentation,Knowledge engineering,Artificial intelligence,Cluster analysis,Recursion,Machine learning | Conference |
Volume | ISSN | ISBN |
2686 | 0302-9743 | 3-540-40210-1 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aureli Soria-Frisch | 1 | 83 | 11.13 |
| Mario Köppen | 2 | 1405 | 166.06 |