Content-Based Image Retrieval using Region Feature Vector


The KIPS Transactions:PartB , Vol. 13, No. 1, pp. 47-52, Feb. 2006
10.3745/KIPSTB.2006.13.1.47,   PDF Download:

Abstract

This paper proposes a method of content-based image retrieval using region feature vector in order to overcome disadvantages of existing color histogram methods. The color histogram methods have a weak point that reduces accuracy because of quantization error, and more. In order to solve this, we convert color information to HSV space and quantize hue factor being purecolor information and calculate histogram and then use this for retrieval feature that is robust in brightness, movement, and rotation. Also we solve an insufficient part that is the most serious problem in color histogram methods by dividing an image into sixteen regions and then comparing each region. We improve accuracy by edge and DC of DCT transformation. As a result of experimenting with 1,000 color images, the proposed method has showed better precision than the existing methods.


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Cite this article
[IEEE Style]
D. W. Kim, Y. J. Song, Y. G. Kim, J. H. Ahn, "Content-Based Image Retrieval using Region Feature Vector," The KIPS Transactions:PartB , vol. 13, no. 1, pp. 47-52, 2006. DOI: 10.3745/KIPSTB.2006.13.1.47.

[ACM Style]
Dong Woo Kim, Young Jun Song, Young Gil Kim, and Jae Hyeong Ahn. 2006. Content-Based Image Retrieval using Region Feature Vector. The KIPS Transactions:PartB , 13, 1, (2006), 47-52. DOI: 10.3745/KIPSTB.2006.13.1.47.