NDLI: Multi-class image annotation approach using particle swarm optimization

Content Provider	IEEE Xplore Digital Library
Author	Sami, M. El-Bendary, N. Hassanien, A.E.
Copyright Year	2012
Description	Author affiliation: Arab Academy for Science, Technology, and Maritime Transport, Cairo, Egypt (El-Bendary, N.) \|\| Faculty of Computers and Information, Cairo University, Egypt (Sami, M.; Hassanien, A.E.)
Abstract	This paper presents an automatic image annotation approach for region labeling. The proposed approach is based on multi-class k-nearest neighbor, K-means, and particle swarm optimization algorithms for feature weighting, in conjunction with normalized cuts based image segmentation technique. This hybrid approach refines the output of multi-class classification that is based on the usage of k-nearest neighbor classifier for automatically labeling image regions from different classes. Each input image is segmented using the normalized cuts segmentation algorithm in order to subsequently create a descriptor for each segment. Particle swarm optimization algorithm is employed as a search strategy to identify an optimal feature subset. Experimental results and comparative performance evaluation, for results obtained from the proposed particle swarm optimization based approach and another support vector machine based approach presented in previous work, demonstrate that the proposed particle swarm optimization based approach outperforms the support vector machine based one, regarding annotation accuracy, for the used dataset.
Starting Page	103
Ending Page	108
File Size	567020
Page Count	6
File Format	PDF
ISBN	9781467351140
e-ISBN	9781467351164
DOI	10.1109/HIS.2012.6421317
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-04
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines K-means Image segmentation Accuracy region labeling k-nearest neighbor (k-NN) image annotation Vectors particle swarm optimization (PSO) Particle swarm optimization Testing Genetic algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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