Content-based Search for Effective Image Retrieval
Pao, H., Fu, H. (2010). Content-based Search for Effective Image Retrieval. EKB Journal Management System, 7(7th International Conference on Electrical Engineering ICEENG 2010), 1-10. doi: 10.21608/iceeng.2010.33291
Hsiao T. Pao; Hsin C. Fu. "Content-based Search for Effective Image Retrieval". EKB Journal Management System, 7, 7th International Conference on Electrical Engineering ICEENG 2010, 2010, 1-10. doi: 10.21608/iceeng.2010.33291
Pao, H., Fu, H. (2010). 'Content-based Search for Effective Image Retrieval', EKB Journal Management System, 7(7th International Conference on Electrical Engineering ICEENG 2010), pp. 1-10. doi: 10.21608/iceeng.2010.33291
Pao, H., Fu, H. Content-based Search for Effective Image Retrieval. EKB Journal Management System, 2010; 7(7th International Conference on Electrical Engineering ICEENG 2010): 1-10. doi: 10.21608/iceeng.2010.33291

Content-based Search for Effective Image Retrieval

The International Conference on Electrical Engineering
Article 119, Volume 7, 7th International Conference on Electrical Engineering ICEENG 2010, May 2010, Pages 1-10    PDF (828.95 K)
Document Type: Original Article
DOI: 10.21608/iceeng.2010.33291
Authors
Hsiao T. Pao1; Hsin C. Fu2
1Dept. of management science, National Chiao-Tung University, Hsinchu, Taiwan, ROC.
2Dept. of computer science, National Chiao-Tung University, Hsinchu, Taiwan, ROC.
Abstract
Abstract:
In this paper we present a content-based approach for effectively searching and
retrieving images. The proposed content-based image query and retrieval (CBQR)
method uses two or more types of query for accessing images --- textual annotation
associated with images and visual appearance, such as color, texture and positional
features of objects in sample images. A user places a keyword-based query first and
then retrieves desired images by visual content-based query. A prototype CBQR system
was implemented and is available at http://140.113.216.66/WebImageSearch for online
demo, and public evaluation. We also conducted experiments over a categorized Corel
image collection and a non-categorized WWW image collection to show the
performance of the proposed CBQR method.
Keywords
Image query and retrieval; Text search; Content-based; Content-based query; Modelbased search
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