@inproceedings{a2acbf2f0ca64e1b92c5cc190a03b18b,
title = "Comparison of multidimensional data access methods for feature-based image retrieval",
abstract = "Within the scope of information retrieval, efficient similarity search in large document or multimedia collections is a critical task. In this paper, we present a rigorous comparison of three different approaches to the image retrieval problem, including cluster-based indexing, distance-based indexing, and multidimensional scaling methods. The time and accuracy tradeoffs for each of these methods are demonstrated on a large Corel image database. Similarity of images is obtained via a featurebased similarity measure using four MPEG-7 low-level descriptors. We show that an optimization of feature contributions to the distance measure can identify irrelevant features and is necessary to obtain the maximum accuracy. We further show that using multidimensional scaling can achieve comparable accuracy, while speeding-up the query times significantly by allowing the use of spatial access methods.",
keywords = "BitMatrix, CBIR, Component, Fastmap, Indexing, LMDS, MPEG-7, Multidimensional access methods, SlimTree",
author = "Serdar Arslan and Ahmet Sa{\c c}an and Esra A{\c c}ar and Toroslu, {I. Hakki} and Adnan Yazici",
year = "2010",
doi = "10.1109/ICPR.2010.797",
language = "English",
isbn = "9780769541099",
series = "Proceedings - International Conference on Pattern Recognition",
pages = "3260--3263",
booktitle = "Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010",
note = "2010 20th International Conference on Pattern Recognition, ICPR 2010 ; Conference date: 23-08-2010 Through 26-08-2010",
}