TY - GEN
T1 - Using keyblock statistics to model image retrieval
AU - Zhu, Lei
AU - Tang, Chun
AU - Zhang, Aidong
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.
PY - 2001
Y1 - 2001
N2 - Keyblock, which is a new framework we proposed for the contentbased image retrieval, is a generalization of the text-based information retrieval technology in the image domain. In this framework, keyblocks, which are analogous to keywords in text document retrieval, can be constructed by exploiting a clustering approach. Then an image can be represented as a list of keyblocks similar to a text document which can be considered as a list of keywords. Based on this image representation, various feature models can be constructed for supporting image retrieval. In this paper, we will conduct keyblock statistic analysis and propose keyblock importance vector to improve the retrieval performance. The statistic analysis is based on the keyblock entropy as well as the keyblock frequency in the image database.
AB - Keyblock, which is a new framework we proposed for the contentbased image retrieval, is a generalization of the text-based information retrieval technology in the image domain. In this framework, keyblocks, which are analogous to keywords in text document retrieval, can be constructed by exploiting a clustering approach. Then an image can be represented as a list of keyblocks similar to a text document which can be considered as a list of keywords. Based on this image representation, various feature models can be constructed for supporting image retrieval. In this paper, we will conduct keyblock statistic analysis and propose keyblock importance vector to improve the retrieval performance. The statistic analysis is based on the keyblock entropy as well as the keyblock frequency in the image database.
UR - https://www.scopus.com/pages/publications/84901753530
U2 - 10.1007/3-540-45453-5_67
DO - 10.1007/3-540-45453-5_67
M3 - Conference contribution
AN - SCOPUS:84901753530
SN - 3540426809
SN - 9783540426806
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 522
EP - 529
BT - Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings
A2 - Shum, Heung-Yeung
A2 - Liao, Mark
A2 - Chang, Shih-Fu
PB - Springer Verlag
T2 - 2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001
Y2 - 24 October 2001 through 26 October 2001
ER -