Authors:
André Homeyer
;
Michael Schwier
and
Horst K. Hahn
Affiliation:
Fraunhofer MEVIS, Germany
Keyword(s):
Image analysis, Image understanding, Classification, Attributed relational graph, Database.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Structural and Syntactic Approach
Abstract:
Object-based image analysis enables the recognition of complex image structures that are intractable to conventional pixel-based methods. To date, there is no generally accepted approach for the object-based processing of images, thus making it difficult to transfer developments. In this paper, we propose a generic concept for object-based image analysis that is broadly applicable and founded on established methodologies, such as the attributed relational graph, the relational data model and statistical classifiers. We also describe a reference implementation of the concept as part of the MeVisLab image processing platform.