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Reseach Article

Optimization Methods used for Automatic Image Annotation/Retrieval: A Survey

by Ashitha Jose, Sreekumar K.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 12
Year of Publication: 2015
Authors: Ashitha Jose, Sreekumar K.
10.5120/ijca2015907613

Ashitha Jose, Sreekumar K. . Optimization Methods used for Automatic Image Annotation/Retrieval: A Survey. International Journal of Computer Applications. 132, 12 ( December 2015), 6-10. DOI=10.5120/ijca2015907613

@article{ 10.5120/ijca2015907613,
author = { Ashitha Jose, Sreekumar K. },
title = { Optimization Methods used for Automatic Image Annotation/Retrieval: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 12 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number12/23644-2015907613/ },
doi = { 10.5120/ijca2015907613 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:29:10.332072+05:30
%A Ashitha Jose
%A Sreekumar K.
%T Optimization Methods used for Automatic Image Annotation/Retrieval: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 12
%P 6-10
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic Image annotation is a dominant research area in computer science. It is concerned with the storage of images and assigning meaningful keywords to it. There are several methods developed for efficient automatic image annotation which uses various optimization techniques. The purpose of this paper is to show the survey study done on the optimization techniques for Image annotation. An image has several preeminent characteristics like colour texture, shape etc. These different descriptors of the images can form a combined feature vector. Optimization algorithms such as Particle swam optimization algorithm, Genetic algorithm etc can be used for optimum feature selection.

References
  1. Ajimi Ameer and SreeKumar.K, Efficient Automatic Image Annotation using Optimized weighted Complementary Feature Fusion using Genetic Algorithm, Second International Symposium on Computer Vision and the Internet (VisionNet’15)
  2. Dong Yang and Ping Guo, Image modeling with combined optimization techniques for image semantic annotation, Springer-Verlag London Limited 2010
  3. Darsana B and G. Jagajothi, Distributed Retrieval of Images using Particle Swarm Optimization and Hadoop, international Journal of Computer Applications (0975 – 8887) Volume 71– No.8, May 2013
  4. Vinay Kumar Lowanshi, Shweta Shrivastava and Vineet Richhariya, An Efficient Approach for Content based Image Retrieval using SVM, KNN-GA as Multilayer Classifier, International Journal of Computer Applications (0975 – 8887) Volume 107 – No. 21, December 2014
  5. Lei Wang and Latifur Khan, Automatic Image Annotation and Retrieval Using Weighted Feature Selection , Multimedia Software Engineering, 2004. Proceedings. IEEE Sixth International Symposium
  6. T.Kanimozhi and K.Latha, A Meta-Heuristic Optimization Approach for Content Based Image Retrieval using Relevance Feedback Method, Proceedings of the World Congress on Engineering 2013 Vol II, WCE 2013, July 3 - 5, 2013, London, U.K.
  7. C.Ramesh babu durai, V.Duraisamy and C.Vinothkumar, Improved Content Based Image Retrieval Using Neural Network Optimization with Genetic Algorithm, International Journal of Emerging Technology and Advanced Engineering (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
  8. S. Bahrami and M. Saniee Abadeh, Automatic image annotation using an evolutionary algorithm, Telecommunications (IST), 2014 7th International Symposium
  9. Rabab M. Ramadan and Rehab F. Abdel – Kader, Face Recognition Using Particle Swarm Optimization-Based Selected Features, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 2, No. 2, June 2009
  10. Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri and Consuelo Gonzalo-Martin, Feature Selection using Particle Swarm Optimization for Thermal Face Recognition, Springer India 2015 R. Chaki et al. (eds.), Applied Computation and Security Systems, Advances in Intelligent Systems and Computing 304, DOI 10.1007/978-81-322-1985-9_2
  11. Sivakumar and Dr.C.Chandrasekar, Modified PSO Based Feature Selection for Classification of Lung CT Images, International Journal of Computer Science and Information Technologies, Vol. 5 (2) , 2014, 2095-2098
  12. Bae-Muu Chang,Hung-Hsu Tsai and Wen-Ling Chou, Using visual features to design a content-based image retrieval method optimized by particle swarm optimization algorithm
Index Terms

Computer Science
Information Sciences

Keywords

Image Annotation Optimization Particle Swam Optimization Content based image retrieval Feature Extraction