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.
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A Generic Concept for Object-based Image Analysis
Semantic Scholar · Computer Science · 2010
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.