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Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval

by Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 16
Year of Publication: 2015
Authors: Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe
10.5120/ijca2015907677

Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe . Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval. International Journal of Computer Applications. 132, 16 ( December 2015), 6-9. DOI=10.5120/ijca2015907677

@article{ 10.5120/ijca2015907677,
author = { Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe },
title = { Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 16 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number16/23676-2015907677/ },
doi = { 10.5120/ijca2015907677 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:29:34.533226+05:30
%A Manasee Kurkure
%A Anuradha Thakare
%A Santvana Gudadhe
%T Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 16
%P 6-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Large amounts of databases are created daily in data storage Due to this it becomes very difficult to retrieve the images require for applications in various fields. Thus Content Based Image Retrieval Techniques play an important character in image processing. Here we will be using various masking methods to find out different features and apply different clustering algorithms. In this paper, we are proposing a hybrid model which is the combination of Genetic and Candidate Group Search algorithm. This gives us the best results in some aspects and find it suitable in point of time and accuracy. Candidate Group search Genetic Algorithm is employed to facilitate the users retrieve the images that are most relevant to the users demand.

References
  1. Cheng Huang Hung, Hua-Min Chiou, Wei-Ning Yang, "Candidate groups search for K-harmonic means data clustering," Applied Mathematical Modelling, Elsevier, 2013.
  2. Anuradha Thakare, Rohini Hanchate, http://research.ijcaonline.org /volume88 /number17 /pxc3894002.pdf, “Introducing Hybrid model for Data Clustering using K-Harmonic Means and Gravitational Search Algorithms,” 2014.
  3. Devendra Kurwe, Prof. Anjna Jayant Deen ,Dr. Rajeev Pandey “A Hybrid Approach for content based image retrieval from large Dataset”, IJCTT) – volume 23 November 1 – May 2015.
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Index Terms

Computer Science
Information Sciences

Keywords

Content based Image Retrieval clustering Feature Extraction Genetic Algorithm Candidate Group search algorithm.