Feature Extraction for Content-based Image Retrievaland Implementation of Image Database Retrieval System


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 8, pp. 1951-1959, Aug. 1998
10.3745/KIPSTE.1998.5.8.1951,   PDF Download:

Abstract

In this paper, we propose an efficient feature extraction method for content-based approach and implement an image retrieval system in the Oracle database. First, we extract color feature by the modified Stricker's method from input images, and this color feature and ART2 neural network are used for the rough classification of images. Next, we extract texture feature using wavelet transform, and finally execute the detailed classification on the rough classified images from the previous step. Using the proposed feature extraction methods, we implement a useful image retrieval system by Extended SQL statement on the relational database. The proposed system is implemented on the Oracle DBMS, and in the experimental results with 200 sample images, it shows the retrieval rate of 90% and 81% in Recall and Precision, respectively.


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Cite this article
[IEEE Style]
K. J. Ah, L. S. Hoon, W. Y. Tae, J. S. Hwan, "Feature Extraction for Content-based Image Retrievaland Implementation of Image Database Retrieval System," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 5, no. 8, pp. 1951-1959, 1998. DOI: 10.3745/KIPSTE.1998.5.8.1951.

[ACM Style]
Kim Jin Ah, Lee Seung Hoon, Woo Yong Tae, and Jung Sung Hwan. 1998. Feature Extraction for Content-based Image Retrievaland Implementation of Image Database Retrieval System. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 5, 8, (1998), 1951-1959. DOI: 10.3745/KIPSTE.1998.5.8.1951.