DocumentCode
3301972
Title
High-performance content-based image retrieval using DFS strategy
Author
Ja-Hwung Su ; Chung-Chieh Hsu ; Ying, Josh Jia-Ching
Author_Institution
Dept. of Inf. Manage., Kainan Univ., Taoyuan, Taiwan
fYear
2013
fDate
13-15 Dec. 2013
Firstpage
270
Lastpage
275
Abstract
Image data is becoming more and more popular due to the prevalence of image capture devices. How to retrieve the images effectively and efficiently from a large number of images has been a challenging issue in recent years. To deal with such issue, the major purpose of this paper is to propose a concept- and content-aware image retrieval approach using Depth-First Search (DFS) strategy to conduct effective and efficient image semantic retrieval. For effectiveness and efficiency, since the search space is reduced into specific subspaces, the retrieval cost is decreased and the retrieval quality is increased. For semantic retrieval, our proposed method can detect the potential concepts to satisfy the user´s semantic need. In the experimental result, it reveals that our proposed approach is more effective and efficient than traditional ones using Breadth-First-Search (BFS) strategy.
Keywords
content-based retrieval; image retrieval; tree searching; DFS strategy; concept-aware image retrieval approach; content-aware image retrieval approach; depth-first search strategy; high-performance content-based image semantic retrieval; image capture devices; image data; retrieval cost reduction; retrieval quality improvement; search space; user semantic need satisfaction; Feature extraction; Image color analysis; Image retrieval; Search engines; Semantics; Visualization; Breadth-First-Search; Depth-First Search; content-based image retrieval; semantic image retrieval; text-based image retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/GrC.2013.6740420
Filename
6740420
Link To Document