NDLI: Image retrieval based on Multi Expression Programming algorithms

Content Provider	IEEE Xplore Digital Library
Author	Weihong Wang Wenrou Lin Qu Li
Copyright Year	2013
Description	Author affiliation: Coll. of Comput. Sci., Zhejiang Univ. of Technol., Hangzhou, China (Weihong Wang; Wenrou Lin; Qu Li)
Abstract	The effectiveness of content-based image retrieval (CBIR) systems can be improved by combining image features or by weighting image similarities, as computed from multiple feature vectors. However, feature combination does not always make sense and the combined similarity function can be more complex than weight-based functions to better satisfy the users' expectations. This paper addressed this problem by presenting a Multi-Expression Programming (MEP) framework to design combined similarity functions. This method allows nonlinear combination of image similarities and is validated through experiments, where the images are retrieved based on the shape of their objects. Experimental results demonstrate that the MEP framework is suitable for the design of effective combinations functions.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	1359
Ending Page	1364
File Size	322140
Page Count	6
File Format	PDF
ISBN	9781467347143
ISSN	21579563
DOI	10.1109/ICNC.2013.6818191
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Image Retrieval MEP Model Image retrieval Programming Feature extraction Image descriptors Vectors Biological cells
Content Type	Text
Resource Type	Article

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