Abstract
Content-based retrieval in image databases requires appropriate features of images to be derived and used in the indexing and searching process. Fast and accurate retrieval is crucial from a user point of view. The kinds of features used, their organization in suitable data structures, and the similarity search scheme, directly affect the speed and quality of content-based retrieval. In this paper, we evaluate the relative significance of three different image features - geometry, moments, and Fourier descriptors in the context of content-based retrieval, and present experimental results. The evaluation metrics are retrieval quality and search time. These could be used to tune the search process which speeds up retrieval without significantly affecting retrieval quality.
Recommended Citation
S. R. Subramanya et al., "Study of Relative Effectiveness of Features in Content-Based Image Retrieval," Proceedings - 1st International Symposium on Cyber Worlds, CW 2002, pp. 168 - 175, article no. 1180876, Institute of Electrical and Electronics Engineers, Jan 2002.
The definitive version is available at https://doi.org/10.1109/CW.2002.1180876
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Content-Based Retrieval; Feature Effectiveness; Image Database; Image Feature
International Standard Book Number (ISBN)
978-076951862-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2002
