DocumentCode :
2791893
Title :
A semantic description for content-based image retrieval
Author :
Wang, Bing ; Zhang, Xin ; Zhao, Xiao-yan ; Zhang, Zhi-de ; Zhang, Hong-xia
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
Volume :
5
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
2466
Lastpage :
2469
Abstract :
Robust and flexible semantic labeling of images is still a basic problem in content-based image representation and retrieval. In this paper, a self-organizing image description model (SID) was put forward for describing the image high-level semantic content. This model is a hierarchical architecture, which includes primitive image layer, image feature layer, image semantic layer, multi-level semantic pattern layer and semantic labeling layer. A semantic-based retrieval algorithm (SBRA) for image high-level semantic content retrieval was designed and implemented. The performance of an experimental image retrieval system is evaluated on a database of around 3000 images. The experimental results show that SID and SBRA are effective in describing image high-level semantic content and can provide flexible image description and efficient image retrieval performance.
Keywords :
content-based retrieval; image representation; image retrieval; content-based image representation; content-based image retrieval; flexible semantic image labeling; hierarchical architecture; image feature layer; image high-level semantic content retrieval; image semantic layer; multi-level semantic pattern layer; primitive image layer; self-organizing image description model; semantic labeling layer; semantic-based retrieval algorithm; Algorithm design and analysis; Content based retrieval; Cybernetics; Educational institutions; Image databases; Image retrieval; Information retrieval; Labeling; Machine learning; Robustness; Content-based image retrieval; Image clusters; Image semantic model; SVM; Semantic description;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620822
Filename :
4620822
Link To Document :
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