Please use this identifier to cite or link to this item: https://doi.org/10.1145/1101149.1101359
Title: MultiPRE: A novel framework with multiple parallel retrieval engines for content-based image retrieval
Authors: Xiong, W.
Qiu, B.
Tian, Q.
Xu, C.
Ong, S.H. 
Foong, K. 
Chevallet, J.-P.
Keywords: Content-based image retrieval
Framework
Fusion
Multilayer
Parallel
PCA
Retrieval engine
Similarity
SVM
Issue Date: 2005
Source: Xiong, W.,Qiu, B.,Tian, Q.,Xu, C.,Ong, S.H.,Foong, K.,Chevallet, J.-P. (2005). MultiPRE: A novel framework with multiple parallel retrieval engines for content-based image retrieval. Proceedings of the 13th ACM International Conference on Multimedia, MM 2005 : 1023-1032. ScholarBank@NUS Repository. https://doi.org/10.1145/1101149.1101359
Abstract: We propose a novel framework for content-based image retrieval with multiple parallel retrieval engines (MultiPRE) to achieve higher retrieval performance. Visual features, including both low-level features, such as color, texture and region features, and middle-level structure features, such as blob representation of objects are used to capture geometrical and statistical characteristics of images. Both clustering analysis and discrimination analysis are used as similarity measures in multiple retrieval engines, which are based on principal component analysis (PCA) and support vector machines (SVM), respectively. Finally outputs of these engines are fused to determine ranking lists of retrieved images for given retrieval topics. The proposed framework has been evaluated based on the 26 image query topics over the CasImage database with over 9000 medical images used in ImageCLEF 2004, an international research effort for content-based image retrieval performance benchmark. Experiments show that the proposed framework achieved significantly better performance in terms of both the mean and the variance of average precision than the best run reported in ImageCLEF2004. Copyright © 2005 ACM.
Source Title: Proceedings of the 13th ACM International Conference on Multimedia, MM 2005
URI: http://scholarbank.nus.edu.sg/handle/10635/71062
ISBN: 1595930442
DOI: 10.1145/1101149.1101359
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