CANDID: comparison algorithm for navigating digital image databases

by: PM Kelly, TM Cannon

Seventh International Working Conference on Scientific and Statistical Database Management (1994), pp. 252-258.

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Uses k-means to cluster image feature vectors.

mthomure (公開 ) - 2008-04-14 02:51:01

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Abstract

In this paper, we propose a method for calculating the similarity between two digital images. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized distance between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to an example target image. This algorithm is applied to the problem of search and retrieval for a database containing pulmonary CT imagery, and experimental results are provided

@inproceedings{citeulike:2665004, abstract = {In this paper, we propose a method for calculating the similarity between two digital images. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized distance between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to an example target image. This algorithm is applied to the problem of search and retrieval for a database containing pulmonary CT imagery, and experimental results are provided}, author = {Kelly, P. M. and Cannon, T. M. }, booktitle = {Scientific and Statistical Database Management, 1994. Proceedings., Seventh International Working Conference on}, citeulike-article-id = {2665004}, comment = {Uses k-means to cluster image feature vectors.}, doi = {10.1109/SSDM.1994.336943}, journal = {Seventh International Working Conference on Scientific and Statistical Database Management}, keywords = {cbir}, pages = {252--258}, posted-at = {2008-04-14 02:51:01}, priority = {2}, title = {CANDID: comparison algorithm for navigating digital image databases}, url = {http://dx.doi.org/10.1109/SSDM.1994.336943}, year = {1994} }

RIS record

TY - CONF ID - citeulike:2665004 L3 - citeulike-article-id:2665004 TI - CANDID: comparison algorithm for navigating digital image databases T2 - Scientific and Statistical Database Management, 1994. Proceedings., Seventh International Working Conference on JF - Seventh International Working Conference on Scientific and Statistical Database Management SP - 252 EP - 258 N2 - In this paper, we propose a method for calculating the similarity between two digital images. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized distance between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to an example target image. This algorithm is applied to the problem of search and retrieval for a database containing pulmonary CT imagery, and experimental results are provided KW - cbir N1 - Uses k-means to cluster image feature vectors. AU - Kelly, PM AU - Cannon, TM PY - 1994/// UR - http://dx.doi.org/10.1109/SSDM.1994.336943 ER -

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