DocumentCode :
938082
Title :
Retrieval for color artistry concepts
Author :
Lay, Jose A. ; Guan, Ling
Author_Institution :
Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
Volume :
13
Issue :
3
fYear :
2004
fDate :
3/1/2004 12:00:00 AM
Firstpage :
326
Lastpage :
339
Abstract :
The paper presents work on the retrieval of artworks for color artistry concepts. First, we confirm the view that the query-by-example paradigm, fundamental to current content-based retrieval systems, is able to extend only limited usefulness. We then propose a concept-based retrieval engine based on the generative grammar of elemental concepts methodology. In the latter, the language by which color artistry concepts are communicated in artworks is used to operate semantic searches. The color artistry language is explicated as elemental concepts and the associated generative grammar. The elemental concepts are used to index the artworks, while the generative grammar is used to facilitate post-coordinate expression of color artistry concept queries by using the elemental concepts.
Keywords :
art; content-based retrieval; image classification; image colour analysis; image retrieval; artwork retrieval; artworks indexing; color artistry concepts; color artistry language; concept-based retrieval engine; content-based retrieval; elemental concepts; generative grammar; query-by-example paradigm; semantic searches; Art; Australia; Content based retrieval; Engines; Humans; Image retrieval; Indexing; Information retrieval; Painting; Abstracting and Indexing as Topic; Algorithms; Archaeology; Archives; Art; Color; Computer Graphics; Culture; Database Management Systems; Databases, Factual; Hypermedia; Image Enhancement; Image Interpretation, Computer-Assisted; Information Dissemination; Information Storage and Retrieval; Internet; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Software; Terminology as Topic; User-Computer Interface;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2003.822971
Filename :
1278357
Link To Document :
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