A Framework for Ocean Satellite Image Classification Based on Ontologies

In this paper we present a framework for ocean image classification based on ontologies. With this aim, we will describe how low and high level content of ocean satellite images can be modeled with an ontology. In addition, we will show how the image classification can be modeled with the ontology in which decision tree based classifiers and rule-based expert systems are represented. Particularly, the rule based expert systems include rules about low-level features (called training and labeling rules), and rules defined from the labeling (called human expert rules). The modeling with the ontology provides an extensible framework in which accommodate several methods of image classification. One of the main aims of our proposal is to provide a mechanism to share data about image classification between applications. We have developed an extensible Protégé plugin to classify images.