Please use this identifier to cite or link to this item:
|Title:||Indexing iconic image database for interactive spatial similarity retrieval||Authors:||Zhou, X.M.
|Issue Date:||2004||Citation:||Zhou, X.M.,Ang, C.H.,Ling, T.W. (2004). Indexing iconic image database for interactive spatial similarity retrieval. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2973 : 314-324. ScholarBank@NUS Repository.||Abstract:||Similarity-based retrieval of images is an important task in many image database applications. Interactive similarity retrieval is one way to resolve the fuzzy area involving psychological and physiological factors of individuals during the retrieval process. A good interactive similarity system is not only dependent on a good measure system, but also closely related to the structure of the image database and the retrieval process based on the respective image database structure. In this paper, we propose to use a digraph of most similar image as an index structure of an iconic spatial similarity retrieval. Our approach makes use of the simple feedback from the user, and avoids the high cost of recomputation of interactive retrieval algorithm. The interactive similarity retrieval process is similar to a guided navigation by the system measure and the user in the image database. The proposed approach prevents looping and guarantees to find the target image. It is straightforward and adaptive to different similarity measure. © Springer-Verlag 2004.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/39714||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 30, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.