Abstract—Algorithms based on granular computing (GrC) have been developed for operations useful in image management. On the other hand, although granular computing has also been applied to development of ontologies, so far there has no well-known research work of using granular computing for development of ontologies in image management. In this paper, we examine this issue, and discuss important aspects need to be considered in a GrC-based approach for integrated ontology development and operations for image management. This examination leads us to further explore its potential implications; in particular, we pay attention to the role of image management as an enabling technology for smart city development, which results in our novel proposal on dual level study of ontologies for smart cities; i.e., macro and micro ontologies. Whereas the macro ontology emphasizes the study of smart cities directly at the infrastructure level, the micro-level ontology exploits features of enabling technologies (such as image management) to the development of smart cities in a more specific way.
Index Terms—Ontology, granular computing, image management.
Zhengxin Chen and Qiuming Zhu are with the Department of Computer Science, University of Nebraska at Omaha, Omaha, NE 68182-0500, USA (e-mail: zchen@unomaha.edu, qzhu@unomaha.edu).
[PDF]
Cite: Zhengxin Chen and Qiuming Zhu, "Granular Computing for Ontologies in Image Management ," International Journal of Knowledge Engineering vol. 6, no. 1, pp. 1-6, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
