Open AccessEfficient Content‐Based Image Retrieval Methods Using Color and Texture
Author(s) -
Lee SangMi,
Bae HeeJung,
Jung SungHwan
Publication year - 1998
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.98.0198.0302
Subject(s) - computer science , artificial intelligence , content based image retrieval , feature extraction , image texture , image retrieval , pattern recognition (psychology) , computer vision , image (mathematics) , discrete cosine transform , feature (linguistics) , image processing , linguistics , philosophy
In this paper, we propose efficient content‐based image retrieval methods using the automatic extraction of the low‐level visual features as image content. Two new feature extraction methods are presented. The first one is an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.