Title :
A Semantic Annotation Algorithm Based on Image Regional Object Ontology
Author :
Lei Shi ; Gu, Guochang ; Liu, Haibo ; Shen, Jing ; Lei Shi
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin
Abstract :
The purpose of this paper is to research the image semantic auto-annotation method, which proposes an image semantic annotation method adopted ontology description and the image regional objects reasoning. First, the image semantic regional description model was build, and then the similar features of the region to achieve the similar semantics were annotated. Second, the algorithm focuses on the image regional object annotation description model which is related to the image semantic annotation description in the model, the spatial relation description relations between semantic objects, objects semantic relations description, abstract level structure and other key technologies, and the overall image semantic annotation would be achieved by semantic reasoning of regional objects. Finally, the search results showed that the method had better semantic retrieval performance.
Keywords :
image retrieval; ontologies (artificial intelligence); semantic networks; image regional object ontology; image semantic auto-annotation; semantic annotation; semantic retrieval; Clustering algorithms; Computer science; Image classification; Image retrieval; Image segmentation; Ontologies; Probability; Software algorithms; Software engineering; Symbiosis; image annotation; object ontology; region semantic;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.625