Please use this identifier to cite or link to this item:
|Title:||ICICLE: A semantic-based retrieval system for WWW images|
|Citation:||Shen, H.T., Tan, K.-L., Zhou, X., Cui, B. (2006). ICICLE: A semantic-based retrieval system for WWW images. Multimedia Systems 11 (5) : 438-454. ScholarBank@NUS Repository. https://doi.org/10.1007/s00530-006-0020-6|
|Abstract:||In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.|
|Source Title:||Multimedia Systems|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 12, 2018
WEB OF SCIENCETM
checked on Oct 2, 2018
checked on Oct 13, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.