A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System


The KIPS Transactions:PartB , Vol. 13, No. 3, pp. 309-314, Jun. 2006
10.3745/KIPSTB.2006.13.3.309,   PDF Download:

Abstract

Recently, multimedia DBMS is appeared to be the core technology of the information society to store, manage and retrieve multimedia data efficiently. In this paper, we propose a new method for content based-retrieval system using wavelet transform, energy value to extract automatically feature vector from image data, and suggest an effective retrieval technique through this method. Wavelet transform is widely used in image compression and digital signal analysis, and its coefficient values reflect image feature very well. The correlation in wavelet domain between query image data and the stored data in database is used to calculate similarity. In order to assess the image retrieval performance, a set of hundreds images are run. The method using standard derivation and mean value used for feature vector extraction are compared with that of our method based on energy value. For the simulation results, our energy value method was more effective than the one using standard derivation and mean value.


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Cite this article
[IEEE Style]
G. H. Yoo and H. S. Kwak, "A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System," The KIPS Transactions:PartB , vol. 13, no. 3, pp. 309-314, 2006. DOI: 10.3745/KIPSTB.2006.13.3.309.

[ACM Style]
Gi Hyoung Yoo and Hoon Sung Kwak. 2006. A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System. The KIPS Transactions:PartB , 13, 3, (2006), 309-314. DOI: 10.3745/KIPSTB.2006.13.3.309.