Image retrieval using texture based on DCT Export

@proceedings{citeulike:1219346, abstract = {A new content-based image retrieval method using texture information is proposed. For efficient image retrieval, it extracts low-level image texture features as a content retrieval index. The proposed feature extraction uses some discrete cosine transform (DCT) coefficients which represent some dominant directions and gray level variations of the image. Our method also uses a hierarchical similarity measure for efficient retrieval, making it possible to reduce the search space in a large image database. In an experiment using a database of 200 images, our method shows a higher performance in the retrieval rate and processing time than Tamura's (1976). Therefore, our approach for extracting features in the transform domain can provide a solution to storage space problem with its ease of computation}, author = {Bae, Hee-Jung and Jung, Sung-Hwan}, citeulike-article-id = {1219346}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=652144}, journal = {Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on}, keywords = {dct, feature-extraction}, pages = {1065--1068 vol.2}, posted-at = {2007-04-10 18:30:55}, priority = {2}, title = {Image retrieval using texture based on DCT}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=652144}, year = {1997} }

TY - CONF ID - citeulike:1219346 L3 - citeulike-article-id:1219346 N2 - A new content-based image retrieval method using texture information is proposed. For efficient image retrieval, it extracts low-level image texture features as a content retrieval index. The proposed feature extraction uses some discrete cosine transform (DCT) coefficients which represent some dominant directions and gray level variations of the image. Our method also uses a hierarchical similarity measure for efficient retrieval, making it possible to reduce the search space in a large image database. In an experiment using a database of 200 images, our method shows a higher performance in the retrieval rate and processing time than Tamura's (1976). Therefore, our approach for extracting features in the transform domain can provide a solution to storage space problem with its ease of computation JF - Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on EP - 1068 vol.2 TI - Image retrieval using texture based on DCT SP - 1065 KW - dct KW - feature-extraction AU - Bae, Hee-Jung AU - Jung, Sung-Hwan PY - 1997/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=652144 ER -