Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

Z. Ren; P. Jensch; W. Ameling

doi:10.1117/12.969267

21 March 1989 Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

Z. Ren, P. Jensch, W. Ameling

Proceedings Volume 1095, Applications of Artificial Intelligence VII; (1989) https://doi.org/10.1117/12.969267
Event: SPIE 1989 Technical Symposium on Aerospace Sensing, 1989, Orlando, FL, United States

Abstract

The success of knowledge-based image analysis methodology and implementation tools depends largely on an appropriately and efficiently built model wherein the domain-specific context information about and the inherent structure of the observed image scene have been encoded. For identifying an object in an application environment a computer vision system needs to know firstly the description of the object to be found in an image or in an image sequence, secondly the corresponding relationships between object descriptions within the image sequence. This paper presents models of image objects scenes by means of hierarchically structured classes. Using the topovisual formalism of graph and higraph, we are currently studying principally the relational aspect and data abstraction of the modeling in order to visualize the structural nature resident in image objects and scenes, and to formalize. their descriptions. The goal is to expose the structure of image scene and the correspondence of image objects in the low level image interpretation. process. The object-based system design approach has been applied to build the model base. We utilize the object-oriented programming language C + + for designing, testing and implementing the abstracted entity classes and the operation structures which have been modeled topovisually. The reference images used for modeling prototypes of objects and scenes are from industrial environments as'well as medical applications.

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Z. Ren, P. Jensch, and W. Ameling "Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); https://doi.org/10.1117/12.969267

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